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Discovery and validation of biomarkers for multiple sclerosis

13 December 2011  •  Author(s): Ole Pless and Sheraz Gul, European ScreeningPort GmbH

Multiple Sclerosis (MS) is an autoimmune disease leading to a chronic inflammation and degeneration of the central nervous system. It is one of the major neurological diseases with approximately 2.5 million suffering patients worldwide. Until now, the underlying mechanisms have not been fully elucidated, but the cause of the disease can be modulated to limit progression and severity. Currently, there are no validated biomarkers available to predict the progression of MS or response to a clinical intervention apart from MRI. In order to identify protein biomarkers for MS as well as other diseases, significant infrastructure is required and this is discussed.

The term ‘biomarker’ has been defined as a “characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention”1,2. The measurement of normal and dysfunctional biological processes and their changes in response to therapeutic intervention forms the basis of biomarkers. The advances in genetics and molecular biology leading to the sequencing of the human genome has resulted in the identification of a variety of novel targets implicated in different disease states3-5. Further technological developments including high throughput profiling of various samples using genomics, transcriptomics and proteomics6,7 has led to the identification of gene and protein based markers that characterise disease states for a number of indications including breast cancer8-10, colorectal cancer11 and cardiovascular diseases12. Additional initiatives that have led to the identification of biomarkers with minimal invasive methods such as proteomics technologies13 and systems biology14 have proven extremely effective for discovering potential biomarkers and drug targets. These technologies tend to provide large data sets that can be difficult to deconvolute for biomarker discovery. This bottleneck can be reduced by using several strategies. The first is to constrict the number of potential biomarkers and drug targets by dividing the proteome into smaller, more biologically significant segments. The second is to widen the bottleneck with higheroutput and higher-throughput screening technologies. The third is to incorporate more preliminary validation into the discovery process. New and emerging technologies provide promise for each of these strategies15.

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