Literature DB >> 17439319

Electrophoretic separations of cerebrospinal fluid proteins in clinical investigations.

Simona D'Aguanno1, Piero Del Boccio, Sergio Bernardini, Enzo Ballone, Carmine Di Ilio, Giorgio Federici, Andrea Urbani.   

Abstract

The cerebrospinal fluid (CSF) is a key sample in the research for novel molecular biomarkers of neurodegenerative disorders. CSF represents a repertoire of neuro-secreted, biosynthesised and metabolised molecular products of the central nervous system (CNS). Diffusion of macromolecules from the peripheral circulatory system to the CSF is highly regulated by the blood-brain barrier, which prevents uncontrolled distribution of proteins in the CNS. The development of reproducible high resolution separations of proteins in 2-D electrophoresis methods by the advent of immobilised pH gradient has opened the route to multivariate holistic protein pattern investigation of CSF into neurodegenerative disorders. Moreover, the introduction of pre-fractionation techniques such as free flow electrophoresis is currently increasing the dynamic depth of proteome analysis. Alzheimer's disease (AD) and other forms of dementia, demyelinating diseases, Parkinson's disease (PD), and Creutzfeldt-Jakob disease (CJD) have been evaluated for biomarker discovery by CSF investigation in multiple studies. However, the statistical design of these clinical cross-sectional investigations remains a limited factor given the strong statistical power required for complex multivariate analysis. These initial evidences are of particular interest in dissecting specific molecular mechanisms. The development of fast and economic profiling of CSF by linear matrix assisted laser desorption ionisation time-of-flight mass spectrometry (MALDI-TOF-MS) is providing a new ancillary technology to assess sample quality and pre-analytical requirements. In the following we take into account all these issues in the CSF proteomics investigation, especially highlighting the possible application in the development of clinical molecular biomarkers.

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Year:  2007        PMID: 17439319     DOI: 10.1515/CCLM.2007.106

Source DB:  PubMed          Journal:  Clin Chem Lab Med        ISSN: 1434-6621            Impact factor:   3.694


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