A comprehensive bioinformatic analysis revealed novel MicroRNA biomarkers of Parkinson's disease

Abstract

Parkinson's disease (PD) is categorized as a neurodegenerative disorder. Different studies have focused on the role of microRNAs (miRNAs) on PD progression. Due to its complexity in initiation and progression, a considerable requirement has arisen to identify novel miRNA biomarkers in a noninvasive manner. In silico analysis has been used to select differentially expressed miRNAs (DE‐miRNAs) and key pathways in this disease. In this manner, several data sets of different neurodegenerative diseases have been analyzed to purify the findings of the present study. Totally, 15 DE miRNAs showed significant changes compared to healthy controls and other neurodegenerative diseases. Then, the targets of the miRNAs were predicted through miRTarBase and TargetScan databases. Besides, enrichment analysis was implemented for predicted target genes. Most of the target genes were enriched in the TRAIL signaling pathway, Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism, protein serine/threonine kinase activity, and Cytoplasm. Moreover, a protein−protein interaction network was constructed to find the most key DE miRNAs and targets in this disease. The results of the present study may help researchers shed light on the discovery of novel biomarkers for PD.

Investigating the role of mitochondrial DNA D-loop variants, haplotypes, and copy number in polycystic ovary syndrome: implications for clinical phenotypes in the Chinese population

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Biomarker potential of competing endogenous RNA networks in Polycystic Ovary Syndrome (PCOS)

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