What makes a prognostic biomarker in CNS diseases: strategies for targeted biomarker discovery? Part 2: chronic progressive and relapsing disease.

INTRODUCTION

Compared with acute neurological conditions, biomarker discovery in chronic progressive and relapsing neurodegenerative diseases may be more difficult. First, the degenerative process may be so slow that the biomarker discovered is released only in small quantities making it a fishing exercise with very little to catch. Second, it may be difficult to differentiate acute new damage, relevant to prognostic estimates, from already existing background damage. A potential advantage in chronic conditions is that there may be sufficient time for the disease to leave a specific signature on the biomarker by the means of post-translational modifications.

AREAS COVERED: In this review, the authors cover chronic and relapsing neurological diseases including multiple sclerosis, neuromyelitis optica, motor neuron disease and a number of neurodegenerative dementias and movement disorders. In these entities, prognostic estimates depend, at least in part, on an accurate differential diagnosis. Therefore, the authors have given particular attention to the added value of biomarkers that can be used in a laboratory setting to support differential diagnosis. Each biomarker was given a class IV rating to demonstrate their prognostic value.

EXPERT OPINION: There has been substantial progress in validating and integrating biomarkers in the diagnostic workup of patients with multiple sclerosis and dementia. New data suggest that prognostic accuracy may be improved in motor neuron disease using protein biomarkers for neurodegeneration. Hypothesis-driven biomarker discovery, which focuses on post-translational modifications such as phosphorylation, aggregate formation or changes in protein stoichiometry, may open new avenues for successful biomarker discovery in chronic and relapsing conditions.