Expression profiling identifies responder and non‐responder phenotypes to interferon‐β in multiple sclerosis
Author(s) -
S Stürzebecher,
KlausPeter Wandinger,
Andreas Rosenwald,
Mohan Sathyamoorthy,
Abraham Tzou,
Pierre Mattar,
Joseph A. Frank,
Louis M. Staudt,
Roland Martinꝉ,
Henry F. McFarland
Publication year - 2003
Publication title -
brain
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.142
H-Index - 336
eISSN - 1460-2156
pISSN - 0006-8950
DOI - 10.1093/brain/awg147
Subject(s) - multiple sclerosis , phenotype , interferon , profiling (computer programming) , gene expression profiling , immunology , biology , computational biology , medicine , genetics , gene expression , gene , computer science , operating system
Autoimmune diseases such as multiple sclerosis are characterized by complex genetic traits and pathomechanisms that translate into clinical heterogeneity. This wide heterogeneity of multiple sclerosis as well as different biological responses to immunomodulatory drugs can be expected to contribute to differential treatment responses. Strategies that dissect the relationship between the treatment response and the biological characteristics in individual patients are valuable not only as a clinical tool, but also in leading to a better understanding of the disease. Here we address the in vitro and ex vivo RNA expression profile under one approved therapy of multiple sclerosis, interferon-beta (IFN-beta, Betaseron), by cDNA microarrays and demonstrate that non-responder and responder phenotypes to IFN-beta as assessed by longitudinal gadolinium-enhanced MRI scans and clinical disease activity differ in their ex vivo gene expression profile. These findings will help to better elucidate the mechanism of action of IFN-beta in relation to different disease patterns and eventually lead to optimized therapy.
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