Literature DB >> 22135858

Identifying candidate genes for Parkinson's disease by integrative genomics method.

Amela Karic1, Rifet Terzic, Alen Karic, Borut Peterlin.   

Abstract

INTRODUCTION: The recent studies of Parkinson's disease (PD) indicate that genetics and environmental factors may play an important role in developing of PD. Nowadays, the cell death and cell adhesion are pathogenetic mechanisms which could be related with PD. On the basis of relationship of those mechanisms with PD, the aim of this study was to identify new candidate genes for PD by integration of results of transcriptomics studies and results obtained by Biomedical Discovery Support System (BITOLA).
MATERIALS AND METHODS: For the detection of functional relationship between potential candidate gene and pathogenetic mechanisms associated with PD, we designed strategy of integration of results of transcriptomics studies with discovery approach in bibliographic data bases and BITOLA. Data of chromosome location, tissue-specific expression, function of potential candidate genes and their association with genetics disorders were obtained from Medline, Locus Link, Gene Cards and OMIM.
RESULTS: Integration and comparison of results obtained using the BITOLA system and analysis of transcriptomics studies identified six genes (MAPT, UCHL1, NSF, CDC42, PARK2 and GFPT1) that occur simultaneously in both group of results. The function of genes NSF, CDC42 and GFPT1 in the pathogenesis of PD has not been studied yet.
CONCLUSIONS: According to our result that aforementioned genes appeared in both groups of results and partially match the criteria set for the selection of candidate genes and their potential role in the development of PD, they should be tested by methods specifically intended for those three genes.

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Year:  2011        PMID: 22135858     DOI: 10.11613/bm.2011.027

Source DB:  PubMed          Journal:  Biochem Med (Zagreb)        ISSN: 1330-0962            Impact factor:   2.313


  6 in total

1.  Regulation of dopamine presynaptic markers and receptors in the striatum of DJ-1 and Pink1 knockout rats.

Authors:  Jianjun Sun; Evguenia Kouranova; Xiaoxia Cui; Robert H Mach; Jinbin Xu
Journal:  Neurosci Lett       Date:  2013-10-22       Impact factor: 3.046

2.  Computational deconvolution of genome wide expression data from Parkinson's and Huntington's disease brain tissues using population-specific expression analysis.

Authors:  Alberto Capurro; Liviu-Gabriel Bodea; Patrick Schaefer; Ruth Luthi-Carter; Victoria M Perreau
Journal:  Front Neurosci       Date:  2015-01-09       Impact factor: 4.677

3.  Genome-wide prediction and prioritization of human aging genes by data fusion: a machine learning approach.

Authors:  Masoud Arabfard; Mina Ohadi; Vahid Rezaei Tabar; Ahmad Delbari; Kaveh Kavousi
Journal:  BMC Genomics       Date:  2019-11-09       Impact factor: 3.969

4.  Identification of biological pathways and genes associated with neurogenic heterotopic ossification by text mining.

Authors:  Yichong Zhang; Yuanbo Zhan; Yuhui Kou; Xiaofeng Yin; Yanhua Wang; Dianying Zhang
Journal:  PeerJ       Date:  2020-01-03       Impact factor: 2.984

Review 5.  The Role of Non-Coding RNAs in the Pathogenesis of Parkinson's Disease: Recent Advancement.

Authors:  Hanwen Zhang; Longping Yao; Zijian Zheng; Sumeyye Koc; Guohui Lu
Journal:  Pharmaceuticals (Basel)       Date:  2022-06-30

6.  Expression levels of specific microRNAs are increased after exercise and are associated with cognitive improvement in Parkinson's disease.

Authors:  Franciele Cascaes Da Silva; Michele Patrícia Rode; Giovanna Grunewald Vietta; Rodrigo Da Rosa Iop; Tânia Beatriz Creczynski-Pasa; Alessandra Swarowsky Martin; Rudney Da Silva
Journal:  Mol Med Rep       Date:  2021-06-29       Impact factor: 2.952

  6 in total

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