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Gene-environment Interaction Models to Unmask Susceptibility Mechanisms in Parkinson's Disease
Published on: January 7, 2014
Identification of key genes and pathways in Parkinson's disease through integrated analysis
Jingru Wang1, Yining Liu1, Tuanzhi Chen1
1Department of Neurology, Liaocheng People's Hospital, Liaocheng Clinical School of Taishan Medical University, Liaocheng, Shandong 252004, P.R. China.
Abstract:
Parkinson's disease (PD) is a progressive, degene-rative neurological disease, typically characterized by tremors and muscle rigidity. The present study aimed to identify differe-ntially expressed genes (DEGs) between patients with PD and healthy patients, and clarify their association with additional biological processes that may regulate factors that lead to PD. An integrated analysis of publicly available Gene Expression Omnibus datasets of PD was performed. DEGs were identified between PD and normal blood samples. Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses, as well as protein‑protein interaction (PPI) networks were used to predict the functions of identified DEGs. Reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR) was performed to validate the predicted expression levels of identified DEGs in whole blood samples obtained from patients with PD and normal healthy controls. A total of 292DEGs were identified between the PD and normal blood samples. Of these, 156 genes were significantly upregulated and 136 genes were significantly downregulated in PD samples following integrated analysis of four PD expression datasets. The 10 most upregulated and downregulated genes were used to construct a PPI network, where ubiquitin C‑terminal hydrolase L1 (UCHL1), 3‑phosphoinositide dependent protein kinase 1 (PDPK1) and protein kinase cAMP‑activated catalytic subunit β (PRKACB) demonstrated the highest connectivity in the network. DEGs were significantly enriched in amoebiasis, vascular smooth muscle contraction, and the Wnt and calcium signaling pathways. The expression levels of significant DEGs, UCHL1, PDPK1 and PRKACB were validated using RT‑qPCR analysis. The findings revealed that UCHL1 and PDPK1 were upregulated and PRKACB was downregulated in patients with PD when compared with normal healthy controls. In conclusion, the results indicate that the significant DEGs, including UCHL1, PDPK1 and PRKACB may be associated with the development of PD. In addition, these factors may be involved in various signaling pathways, including amoebiasis, vascular smooth muscle contraction and the Wnt and calcium signaling pathways.
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