Literature DB >> 28004338

Network Analysis Identifies Disease-Specific Pathways for Parkinson's Disease.

Chiara Monti1,2, Ilaria Colugnat1, Leonardo Lopiano3, Adriano Chiò3, Tiziana Alberio4,5.   

Abstract

Neurodegenerative diseases are characterized by the progressive loss of specific neurons in selected regions of the central nervous system. The main clinical manifestation (movement disorders, cognitive impairment, and/or psychiatric disturbances) depends on the neuron population being primarily affected. Parkinson's disease is a common movement disorder, whose etiology remains mostly unknown. Progressive loss of dopaminergic neurons in the substantia nigra causes an impairment of the motor control. Some of the pathogenetic mechanisms causing the progressive deterioration of these neurons are not specific for Parkinson's disease but are shared by other neurodegenerative diseases, like Alzheimer's disease and amyotrophic lateral sclerosis. Here, we performed a meta-analysis of the literature of all the quantitative proteomic investigations of neuronal alterations in different models of Parkinson's disease, Alzheimer's disease, and amyotrophic lateral sclerosis to distinguish between general and Parkinson's disease-specific pattern of neurodegeneration. Then, we merged proteomics data with genetics information from the DisGeNET database. The comparison of gene and protein information allowed us to identify 25 proteins involved uniquely in Parkinson's disease and we verified the alteration of one of them, i.e., transaldolase 1 (TALDO1), in the substantia nigra of 5 patients. By using open-source bioinformatics tools, we identified the biological processes specifically affected in Parkinson's disease, i.e., proteolysis, mitochondrion organization, and mitophagy. Eventually, we highlighted four cellular component complexes mostly involved in the pathogenesis: the proteasome complex, the protein phosphatase 2A, the chaperonins CCT complex, and the complex III of the respiratory chain.

Entities:  

Keywords:  Alzheimer’s disease; Amyotrophic lateral sclerosis; Meta-analysis; Network analysis; Parkinson’s disease; Pathway analysis

Mesh:

Year:  2016        PMID: 28004338     DOI: 10.1007/s12035-016-0326-0

Source DB:  PubMed          Journal:  Mol Neurobiol        ISSN: 0893-7648            Impact factor:   5.590


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