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Brain Advance Access published online on May 6, 2003
Brain, doi:10.1093/brain/awg147
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© 2003 The Guarantors of Brain

Article

Expression profiling identifies responder and non-responder phenotypes to interferon-{beta} in multiple sclerosis

S. Stürzebecher 1, K. P. Wandinger 2, A. Rosenwald 3, M. Sathyamoorthy 3, A. Tzou 2, P. Mattar 2, J. A. Frank 4, L. Staudt 3, R. Martin 2*, H. F. McFarland 2

1 Neuroimmunology Branch, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA ; SBU Therapeutics, Schering AG, Berlin, Germany
2 Neuroimmunology Branch, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
3 Metabolism Branch, National Cancer Institute, Bethesda, MD, USA
4 Laboratory of Diagnostic Radiology Research, Clinical Center, National Institutes of Health, Bethesda, MD, USA

* Corresponding author. E-mail: martinr{at}ninds.nih.gov.

Received 7 August 2002 ; revised 28 January 2003 ; accepted 3 February 2003

Abstract

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.

Keywords: cDNA microarrays; expression profile; interferon-{beta}; multiple sclerosis
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