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Mitochondrial Pathology in Parkinson's Disease
Author(s) -
Schapira Anthony H. V.
Publication year - 2011
Publication title -
mount sinai journal of medicine: a journal of translational and personalized medicine
Language(s) - English
Resource type - Journals
eISSN - 1931-7581
pISSN - 0027-2507
DOI - 10.1002/msj.20303
Subject(s) - parkinson's disease , pathogenesis , disease , medicine , bioinformatics , parkinsonism , mitochondrion , mitochondrial dna , parkin , genetics , alpha synuclein , mutation , oxidative stress , neurodegeneration , etiology , neuroscience , gene , biology , pathology
The last 25 years have witnessed remarkable advances in our understanding of the etiology and pathogenesis of Parkinson's disease. The ability to undertake detailed biochemical analyses of the Parkinson's disease postmortem brain enabled the identification of defects of mitochondrial and free‐radical metabolism. The discovery of the first gene mutation for Parkinson's disease, in alpha‐synuclein, ushered in the genetic era for the disease and the subsequent finding of several gene mutations causing parkinsonism, 15 at the time of writing. Technological advances both in sequencing technology and software analysis have allowed association studies of sufficiently large size accurately to describe genes conferring an increased risk for Parkinson's disease. What has been so surprising is the convergence of these 2 separate disciplines (biochemistry and genetics) in terms of reinforcing the importance of the same pathways (ie, mitochondrial dysfunction and free‐radical metabolism). Other pathways are also important in pathogenesis, including protein turnover, inflammation, and post‐translational modification, particularly protein phosphorylation and ubiquitination. However, even these additional pathways overlap with each other and with those of mitochondrial dysfunction and oxidative stress. This review explores these concepts with particular relevance to mitochondrial involvement. Mt Sinai J Med 78:872–881, 2011. © 2011 Mount Sinai School of Medicine

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