Abstract
The identification of biomarkers for early diagnosis of Parkinson's disease (PD) prior to the onset of symptoms may improve the effectiveness of therapy. To identify potential biomarkers, we downloaded microarray datasets of PD from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between PD and normal control (NC) groups were obtained, and the feature selection procedure and classification model were used to identify optimal diagnostic gene biomarkers for PD. A total of 1229 genes (640 up‐regulated and 589 down‐regulated) were obtained for PD, and nine DEGs (PTGDS,GPX3,SLC25A20,CACNA1D,LRRN3,POLR1D,ARHGAP26,TNFSF14 and VPS11) were selected as optimal PD biomarkers with great diagnostic value. These nine DEGs were significantly enriched in regulation of circadian sleep/wake cycle, sleep and gonadotropin‐releasing hormone signaling pathway. Finally, we examined the expression of GPX3,SLC25A20,LRRN3 and POLR1D in blood samples of patients with PD by qRT‐PCR. GPX3,LRRN3 and POLR1D exhibited the same expression pattern as in our analysis. In conclusion, this study identified nine DEGs that may serve as potential biomarkers of PD.
Highlights
The identification of biomarkers for early diagnosis of Parkinson’s disease (PD) prior to the onset of symptoms may improve the effectiveness of therapy
We identified differentially expressed gene (DEG) by comparison between patients with PD and normal control (NC) groups by performing an integrated analysis of multiple microarray datasets
The microarray datasets of PD were retrieved from the Gene Expression Omnibus (GEO) database by searching keywords (‘parkinson disease’ [MeSH Terms] OR Parkinson’s disease [All Fields]) AND ‘Homo sapiens’ [porgn] AND ‘gse’ [Filter]
Summary
The identification of biomarkers for early diagnosis of Parkinson’s disease (PD) prior to the onset of symptoms may improve the effectiveness of therapy. A total of 1229 genes (640 up-regulated and 589 down-regulated) were obtained for PD, and nine DEGs (PTGDS, GPX3, SLC25A20, CACNA1D, LRRN3, POLR1D, ARHGAP26, TNFSF14 and VPS11) were selected as optimal PD biomarkers with great diagnostic value. With advances in various high-throughput technologies, a number of key genes have been identified as diagnostic or prognostic biomarkers for various diseases, such as cancer and neurodegenerative disorders, Abbreviations ARHGAP26, Rho GTPase activating protein 26; AUC, area under the ROC curve; CACNA1D, calcium voltage-gated channel subunit alpha1D; DEG, differentially expressed gene; FDR, false discovery rate; GEO, Gene Expression Omnibus; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; MJD, Machado–Joseph disease; NC, normal control; PD, Parkinson’s disease; PPI, protein–protein interaction; PTGDS, prostaglandin D2 synthase; qRT-PCR, quantitative real-time polymerase chain reaction; ROC, receiver operating characteristic; SVM, support vector machine; TNFSF14, TNF superfamily member 14; VGCC, voltage-gated calcium channel. Compared with a single microarray study, integrated analysis of multiple microarrays could identify differentially expressed genes (DEGs) with more accuracy, and increase the statistical power
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