The Potential Circular RNAs Biomarker Panel and Regulatory Networks of Parkinson's Disease

Yousheng Xiao; Hongchang Chen; Jiajia Liao; Qinxin Zhang; Honghu He; Jiang Lei; Jinjun Huang; Qiang Ouyang; Yuefei Shen; Jin Wang

doi:10.3389/fnins.2022.893713

The Potential Circular RNAs Biomarker Panel and Regulatory Networks of Parkinson's Disease

Front Neurosci. 2022 May 13:16:893713. doi: 10.3389/fnins.2022.893713. eCollection 2022.

Authors

Yousheng Xiao¹, Hongchang Chen^{1

2}, Jiajia Liao¹, Qinxin Zhang¹, Honghu He¹, Jiang Lei¹, Jinjun Huang³, Qiang Ouyang², Yuefei Shen¹, Jin Wang¹

Affiliations

¹ Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
² Department of Neurology, Minzu Hospital of Guangxi Zhuang Autonomous Region, Nanning, China.
³ Department of Rehabilitation, Guiping People's Hospital, Guiping, China.

Abstract

Parkinson's disease (PD) is a progressive neurodegenerative disease. It has been reported that circular RNAs (circRNAs) play important roles in several neurological diseases. However, the role and regulatory networks of circRNAs in PD are still largely unclear. In this study, we first compared the global expression level of circRNAs from patients with PD and controls using microarray, then the candidate circRNAs were validated in another PD cohort. The possible functions of these candidate circRNAs were analyzed using Gene Ontology (GO) analyses and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, and the regulatory networks of these candidate circRNAs were constructed through circRNA-miRNA-mRNA regulatory networks, protein-protein interaction (PPI) networks, and transcription factor-circRNA networks. The results indicated that hsa_circRNA_101275, hsa_circRNA_103730, and hsa_circRNA_038416 were significantly more highly expressed in patients with PD, while hsa_circRNA_102850 was lower expressed in patients with PD when compared with controls. A circRNA panel combining the four differentially expressed circRNA showed a high diagnostic ability to distinguish patients with PD from controls (AUC = 0.938). Furthermore, GO and KEGG analysis showed these candidate circRNAs were enriched in PI3K-Akt and MAPK signaling pathways. We established circRNA-miRNA-mRNA regulatory networks and identified 10 hub genes (ESR1, PTEN, SHC1, IGF1R, SMAD2, KRAS, MDM2, HIF1A, BMP4, and ACVR2B) were closely related to PD by using PPI network analysis. Besides, these circRNAs were predicted to be regulated through tyrosine hydroxylase (TH)-relevant transcription factors such as GATA2 and GATA3. In conclusion, our results suggest that the circRNA panel and the established circRNA-miRNA-mRNA regulation networks might provide potential novel biomarkers and therapeutic targets for PD.

Keywords: Parkinson’s disease; bioinformatics; biomarker; circular RNA; diagnosis; regulatory networks.