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Current Proteomics

Editor-in-Chief

ISSN (Print): 1570-1646
ISSN (Online): 1875-6247

Proteomics as Applied to Inherited Metabolic Diseases

Author(s): Eva Richard, Alejandra Gamez, Pedro Ruiz-Sala, Belen Perez, Lourdes R. Desviat and Magdalena Ugarte

Volume 6, Issue 3, 2009

Page: [140 - 153] Pages: 14

DOI: 10.2174/157016409789351897

Price: $65

Abstract

Inherited metabolic diseases (IMD) include a broad spectrum of biochemical alterations caused by genetic defects which affect the structure and function of proteins involved in cellular metabolic pathways. Until now, more than 500 different IMD that alter the synthesis, metabolism, transport and/or storage of biochemical compounds have been identified. Molecular and biochemical techniques can be applied to determine both the genotype and phenotype of IMD patients; they allow for accurate diagnosis and application of individual based treatment strategies. The emerging genomic, proteomic and metabolomic tools using molecular, cellular and physiological approaches provide deeper insight into the pathophysiology of metabolic diseases. Mass spectrometry is a powerful and established technology, employed in IMD research and newborn screening that leads to early diagnosis of different metabolic disorders. Over the last years, the number of different proteomic techniques applied to IMD investigation has dramatically increased. The most remarkable ones include: 2-DE and LC for protein separation; and ESI-MS, ESI-MS/MS, MALDI-MS, MALDI-MS/MS, SELDI-MS, DIOS-MS for protein/metabolite identification and analysis. Proteomics offers the ability to identify novel proteins and to study their expression patterns and function, along with the potential to discover biomarkers as diagnostic tools or for the development of new therapeutic strategies. This review describes the main proteomic techniques applied to IMD diagnosis and research.

Keywords: Inherited metabolic diseases, proteomics, mass spectrometry, protein profiling, biomarkers, quantitative proteomics, functional proteomics

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