OBJECTIVES: Interferon IFN-beta is indicated for the treatment of multiple sclerosis. A significant proportion of patients show a poor clinical response to therapy. Type I interferon exerts its effect at least partially through interaction of specific transcription factors with interferon-stimulated response elements (ISREs), mostly located in promoter regions of its target genes. We hypothesized that polymorphisms may occur within or close to ISRE elements, altering type I interferon inducibility and ultimately leading to a modified clinical response in carriers. METHODS: We selected 100 ISRE-containing genes and sequenced their promoter regions in small genomic deoxyribonucleic acid pools of responding and nonresponding patients, as well as healthy control subjects. A selection of polymorphisms discovered by this approach was scrutinized subsequently in a collection of individual deoxyribonucleic acid samples. RESULTS: We identified 4 genes containing polymorphisms associated with response to recombinant IFN-beta: IFNAR1 (P = .036), LMP7 (P = .002; odds ratio [OR], 6.37 [95% confidence interval (CI), 1.84-24.1]), CTSS (P = .02; OR, 0.38 [95% CI, 0.18-0.84]), and MxA (P = .015; OR, 3.37 [95% CI, 1.11-11.4]). Logistic regression analysis with treatment outcome used as the dependent variable and genotype as the independent variable revealed 2 genes, LMP7 (OR, 0.55 [95% CI, 0.34-0.89]) and MxA (OR, 0.41 [95% CI, 0.19-0.88]), that were independently associated with treatment response. CONCLUSIONS: Our work confirms and extends previous indications for a polygenic mechanism involved in bringing about responsiveness to recombinant IFN-beta. The identification of 2 genes active in the antigen processing and presentation cascade; that is, LMP7, coding for the proteasome subunit beta, and CTSS, coding for cathepsin S; as potential response modifiers may identify this pathway as being of particular relevance to phenotypic expression of response heterogeneity.
OBJECTIVES: Interferon IFN-beta is indicated for the treatment of multiple sclerosis. A significant proportion of patients show a poor clinical response to therapy. Type I interferon exerts its effect at least partially through interaction of specific transcription factors with interferon-stimulated response elements (ISREs), mostly located in promoter regions of its target genes. We hypothesized that polymorphisms may occur within or close to ISRE elements, altering type I interferon inducibility and ultimately leading to a modified clinical response in carriers. METHODS: We selected 100 ISRE-containing genes and sequenced their promoter regions in small genomic deoxyribonucleic acid pools of responding and nonresponding patients, as well as healthy control subjects. A selection of polymorphisms discovered by this approach was scrutinized subsequently in a collection of individual deoxyribonucleic acid samples. RESULTS: We identified 4 genes containing polymorphisms associated with response to recombinant IFN-beta: IFNAR1 (P = .036), LMP7 (P = .002; odds ratio [OR], 6.37 [95% confidence interval (CI), 1.84-24.1]), CTSS (P = .02; OR, 0.38 [95% CI, 0.18-0.84]), and MxA (P = .015; OR, 3.37 [95% CI, 1.11-11.4]). Logistic regression analysis with treatment outcome used as the dependent variable and genotype as the independent variable revealed 2 genes, LMP7 (OR, 0.55 [95% CI, 0.34-0.89]) and MxA (OR, 0.41 [95% CI, 0.19-0.88]), that were independently associated with treatment response. CONCLUSIONS: Our work confirms and extends previous indications for a polygenic mechanism involved in bringing about responsiveness to recombinant IFN-beta. The identification of 2 genes active in the antigen processing and presentation cascade; that is, LMP7, coding for the proteasome subunit beta, and CTSS, coding for cathepsin S; as potential response modifiers may identify this pathway as being of particular relevance to phenotypic expression of response heterogeneity.
Authors: Catherine O'Doherty; Alexander Favorov; Shirley Heggarty; Colin Graham; Olga Favorova; Michael Ochs; Stanley Hawkins; Michael Hutchinson; Killian O'Rourke; Koen Vandenbroeck Journal: Pharmacogenomics Date: 2009-07 Impact factor: 2.533
Authors: Matthias Habjan; Andreas Pichlmair; Richard M Elliott; Anna K Overby; Timo Glatter; Matthias Gstaiger; Giulio Superti-Furga; Hermann Unger; Friedemann Weber Journal: J Virol Date: 2009-02-11 Impact factor: 5.103