Dataset Information

Identification of Parkinson's disease-related pathways and potential risk factors.

ABSTRACT: OBJECTIVE:To identify Parkinson's disease (PD)-associated deregulated pathways and genes, to further elucidate the pathogenesis of PD. METHODS:Dataset GSE100054 was downloaded from the Gene Expression Omnibus, and differentially expressed genes (DEGs) in PD samples were identified. Functional enrichment analyses were conducted for the DEGs. The top 10 hub genes in the protein-protein interaction (PPI) network were screened out and used to construct a support vector machine (SVM) model. The expression of the top 10 genes was then validated in another dataset, GSE46129, and a clinical patient cohort. RESULTS:A total of 333 DEGs were identified. The DEGs were clustered into two gene sets that were significantly enriched in 12 pathways, of which 8 were significantly deregulated in PD, including cytokine-cytokine receptor interaction, gap junction, and actin cytoskeleton regulation. The signature of the top 10 hub genes in the PPI network was used to construct the SVM model, which had high performance for predicting PD. Of the 10 genes, GP1BA, GP6, ITGB5, and P2RY12 were independent risk factors of PD. CONCLUSION:Genes such as GP1BA, GP6, P2RY12, and ITGB5 play critical roles in PD pathology through pathways including cytokine-cytokine receptor interaction, gap junctions, and actin cytoskeleton regulation.

SUBMITTER: Shen J

PROVIDER: S-EPMC7543192 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of Parkinson's disease-related pathways and potential risk factors.

Shen Jun J Chen Xiao-Chang XC Li Wang-Jun WJ Han Qiu Q Chen Chun C Lu Jing-Min JM Zheng Jin-Yu JY Xue Shou-Ru SR

The Journal of international medical research 20201001 10

<h4>Objective</h4>To identify Parkinson's disease (PD)-associated deregulated pathways and genes, to further elucidate the pathogenesis of PD.<h4>Methods</h4>Dataset GSE100054 was downloaded from the Gene Expression Omnibus, and differentially expressed genes (DEGs) in PD samples were identified. Functional enrichment analyses were conducted for the DEGs. The top 10 hub genes in the protein-protein interaction (PPI) network were screened out and used to construct a support vector machine (SVM) m ...[more]

PMID: 33021140

Similar Datasets

Project description: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 ? (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.

Dataset Information

Identification of Parkinson's disease-related pathways and potential risk factors.

Publications

Identification of Parkinson's disease-related pathways and potential risk factors.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets