Table of Contents Author Guidelines Submit a Manuscript
Autoimmune Diseases
Volume 2011, Article ID 932351, 12 pages
Review Article

Heterogeneity in Multiple Sclerosis: Scratching the Surface of a Complex Disease

1Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Headington, Oxford, OX3 7BN, UK
2Department of Clinical Neurology, University of Oxford, The West Wing, John Radcliffe Hospital, Oxford, OX3 9DU, UK
3Nuffield Department of Clinical Medicine, University of Oxford, Henry Wellcome Building for Molecular Physiology, Old Road Campus, Headington, Oxford OX3 7BN, UK

Received 8 September 2010; Accepted 27 October 2010

Academic Editor: Sreeram Ramagopalan

Copyright © 2011 Giulio Disanto et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Multiple Sclerosis (MS) is the most common demyelinating disease of the central nervous system. Although the etiology and the pathogenesis of MS has been extensively investigated, no single pathway, reliable biomarker, diagnostic test, or specific treatment have yet been identified for all MS patients. One of the reasons behind this failure is likely to be the wide heterogeneity observed within the MS population. The clinical course of MS is highly variable and includes several subcategories and variants. Moreover, apart from the well-established association with the HLA-class II DRB1*15:01 allele, other genetic variants have been shown to vary significantly across different populations and individuals. Finally both pathological and immunological studies suggest that different pathways may be active in different MS patients. We conclude that these “MS subtypes” should still be considered as part of the same disease but hypothesize that spatiotemporal effects of genetic and environmental agents differentially influence MS course. These considerations are extremely relevant, as outcome prediction and personalised medicine represent the central aim of modern research.