Biomarkers for multiple sclerosis.

Abstract

The pursuit of personalized medicine requires the development of biomarkers to predict disease course, monitor disease evolution, stratify patient subgroups by disease activity and to predict and monitor response to therapies. Multiple sclerosis (MS) is a common neurological disease in young adults with an unpredictable course that may be associated with significant disability, diminishing the patient's quality of life. Currently, disease prognosis is based on clinical information (relapse rate and disability scales) and diagnostic tests (brain MRI or the presence of oligoclonal bands in the cerebrospinal fluid). However, the ability of neurologists to make an accurate prognosis is very limited based on such information, a situation perceived by patients as one of their biggest concerns. Although many recent studies have identified different molecules and imaging techniques associated with the course of MS, in most cases the diagnostic accuracy of such technologies has not been properly assessed. This shortcoming is partly due to the failure to validate such biomarkers, which impedes their application in clinical practice. However, the recent validation of anti-aquaporin-4 antibodies for Devic's disease and the development of optic coherent tomography for MS, are examples of the benefits that the development of MS biomarkers can offer. Indeed, it may currently be necessary to redress the bias in research towards clinical validation rather than discovery in order to promote translational research and improve patient's quality of life.