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. 2018 Jun 18:10:178.
doi: 10.3389/fnagi.2018.00178. eCollection 2018.

Integrated Analysis and Identification of Novel Biomarkers in Parkinson's Disease

Jieshan Chi  1   2 , Qizhi Xie  1   2 , Jingjing Jia  1 , Xiaoma Liu  1 , Jingjing Sun  1 , Yuanfei Deng  1   3 , Li Yi  1   3
Affiliations

Integrated Analysis and Identification of Novel Biomarkers in Parkinson's Disease

Jieshan Chi et al. Front Aging Neurosci. .

Abstract

Parkinson's disease (PD) is a quite common neurodegenerative disorder with a prevalence of approximately 1:800-1,000 in subjects over 60 years old. The aim of our study was to determine the candidate target genes in PD through meta-analysis of multiple gene expression arrays datasets and to further combine mRNA and miRNA expression analyses to identify more convincing biological targets and their regulatory factors. Six included datasets were obtained from the Gene Expression Omnibus database by systematical search, including five mRNA datasets (150 substantia nigra samples in total) and one miRNA dataset containing 32 peripheral blood samples. A chip meta-analysis of five microarray data was conducted by using the metaDE package and 94 differentially expressed (DE) mRNAs were comprehensively obtained. And 19 deregulated DE miRNAs were obtained through the analysis of one miRNAs dataset by Qlucore Omics Explorer software. An interaction network formed by DE mRNAs, DE miRNAs, and important pathways was discovered after we analyzed the functional enrichment, protein-protein interactions, and miRNA targetome prediction analysis. In conclusion, this study suggested that five significantly downregulated mRNAs (MAPK8, CDC42, NDUFS1, COX4I1, and SDHC) and three significantly downregulated miRNAs (miR-126-5p, miR-19-3p, and miR-29a-3p) were potentially useful diagnostic markers in clinic, and lipid metabolism (especially non-alcoholic fatty liver disease pathway) and mitochondrial dysregulation may be the keys to biochemically detectable molecular defects. However, the role of these new biomarkers and molecular mechanisms in PD requires further experiments in vivo and in vitro and further clinical evidence.

Keywords: NAFD pathway; Parkinson’s disease; bioinformatics; biomarkers; genes; miRNA.

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Figures

FIGURE 1
FIGURE 1
(A) Quality control result. (B) DE genes through the method of meta-DE. (For the sake of space, only a part of the figure is shown here. The full size figure is displayed in Online Resource Supplementary Figure S1.
FIGURE 2
FIGURE 2
Functional enrichment analysis of meta-DE genes. (A) Cellular components of GO enrichment analysis. (B) Biological processes of GO enrichment analysis. (C) Molecular functions of GO enrichment analysis. (D) KEGG pathway enrichment analysis.
FIGURE 3
FIGURE 3
PPI networks. (A) PPI network of overlap DE genes. (B) PPI network of meta-DE genes. The size and color of map nodes are determined by the degree value, which renders a gradual process by setting the small size with a low degree in green, large size with a high degree in orange.
FIGURE 4
FIGURE 4
Summary results of the consensus of targets genes of top five miRNAs.
FIGURE 5
FIGURE 5
The interaction between miRNAs and genes. (A) The relationship of gene–gene and gene–miRNA. (B) The outline of the interaction between the significant KEGG pathways of meta-DE genes and miRNAs.
See this image and copyright information in PMC

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