Application of quantitative proteomics technologies to the biomarker discovery pipeline for multiple sclerosis

Authors

  • Laura F. Dagley,

    1. Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria, Australia
    2. Banting and Best Department of Medical Research, Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
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  • Andrew Emili,

    1. Banting and Best Department of Medical Research, Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
    2. Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
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  • Anthony W. Purcell

    Corresponding author
    1. Department of Biochemistry and Molecular Biology, Monash University, Clayton, Victoria, Australia
    • Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria, Australia
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Correspondence: Professor Anthony W. Purcell, Department of Biochemistry and Molecular Biology, Monash University, Clayton, Victoria, 3800, Australia

E-mail: anthony.purcell@monash.edu

Fax: + 61-03-9902-9500

Abstract

Multiple sclerosis is an inflammatory-mediated demyelinating disorder most prevalent in young Caucasian adults. The various clinical manifestations of the disease present several challenges in the clinic in terms of diagnosis, monitoring disease progression and response to treatment. Advances in MS-based proteomic technologies have revolutionized the field of biomarker research and paved the way for the identification and validation of disease-specific markers. This review focuses on the novel candidates discovered by the application of quantitative proteomics to relevant disease-affected tissues in both the human context and within the animal model of the disease known as experimental autoimmune encephalomyelitis. The role of targeted MS approaches for biomarker validation studies, such as multiple reaction monitoring will also be discussed.

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