Identification of therapeutic targets for Parkinson's disease via bioinformatics analysis

Dong,Na; Zhang,Xueqing; Liu,Qingjun

doi:10.3892/mmr.2016.6044

Identification of therapeutic targets for Parkinson's disease via bioinformatics analysis

Authors:
- Na Dong
- Xueqing Zhang
- Qingjun Liu
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Affiliations: Department of Nerve Electrophysiology, Tianjin Huanhu Hospital, Tianjin 300060, P.R. China
Published online on: December 14, 2016 https://doi.org/10.3892/mmr.2016.6044
Pages: 731-735
Copyright: © Dong et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

The present study aimed to identify molecular targets that have important roles in the progression of Parkinson's disease. The gene expression profile dataset GSE7621 and the microRNA (miRNA) expression profile dataset GSE16658 were downloaded from the Gene Expression Omnibus database. R programing software was used to identify differentially expressed genes and miRNAs. Subsequently, enriched Gene Ontology terms of differentially expressed genes were obtained using the Database for Annotation, Visualization and Integrated Discovery. Target genes of differentially expressed miRNAs were identified using the starBase database and a miRNA‑gene regulatory network was constructed using Cytoscape software. A total of 391 differentially expressed genes and 88 differentially expressed miRNAs were identified. Gene Ontology terms that were associated with nervous system activity, including synapse and dopamine metabolic process, were shown to be enriched in the differentially expressed genes. A total of 620 target genes were identified from the differentially expressed miRNAs, and 10 overlaps were identified between these target genes and differentially expressed genes. Furthermore, 10 miRNA‑gene regulation pairs were obtained between the overlaps and differentially expressed miRNAs. In conclusion, the present study used bioinformatics analysis of gene and miRNA expression profile datasets, and identified potential therapeutic targets for Parkinson's disease.

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