4.1 Review

Clinical proteomics for diagnosis and typing of systemic amyloidoses

Journal

PROTEOMICS CLINICAL APPLICATIONS
Volume 7, Issue 1-2, Pages 136-143

Publisher

WILEY-V C H VERLAG GMBH
DOI: 10.1002/prca.201200097

Keywords

Amyloidosis typing; Clinical proteomics; Laser microdissection (LMD); MudPIT; Quantitative analysis

Funding

  1. Italian Ministry of Economy and Finance
  2. Italian Ministry of University and Research
  3. Fondazione Cariplo [2010-0653, 2009-3149]
  4. AIRC (Associazione Italiana per la Ricerca sul Cancro) [9965]
  5. Amyloid Foundation
  6. Fondazione Mintas, Ghislieri College, Pavia, Italy

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Amyloidoses are characterized by deposition of misfolded proteins as beta-pleated sheet fibrils in organs. Despite the similar morphologic appearance of fibrils, at least 28 different proteins have been identified as causative agents of amyloidosis in humans, 14 of which responsible for systemic forms. Correct identification of the amyloidogenic proteins in each patient is crucial for clinical management, in order to avoid misdiagnosis, inappropriate treatment, and to assess the prognosis. Amyloidosis, being essentially a protein deposition disorder, is an attractive venue for the application of proteomics methodologies; among the different possible analytic goals, the most important is the unequivocal diagnosis and typing of the amyloid deposits. Amyloidosis typing has been traditionally based on a multidisciplinary approach, requiring detailed clinical evaluation and immunohistochemical studies together with biochemical and genetic tests. However, drawbacks of immunohistochemistry-based techniques have driven the search for alternative methods for direct amyloid typing. In particular, MS-based proteomics, recently introduced in the clinical practice with or without the previous 2DE separation of proteins, has revolutionized amyloid typing. This review provides a description of current proteomics methods for the identification of the amyloidogenic proteins, with special attention to the most innovative MS-based techniques.

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