Integrated bioinformatics analysis for exploring potential biomarkers related to Parkinson's disease progression

BMC Med Genomics. 2024 May 17;17(1):133. doi: 10.1186/s12920-024-01885-9.

Abstract

Background: Parkinson's disease (PD) is a progressive neurodegenerative disease with increasing prevalence. Effective diagnostic markers and therapeutic methods are still lacking. Exploring key molecular markers and mechanisms for PD can help with early diagnosis and treatment improvement.

Methods: Three datasets GSE174052, GSE77668, and GSE168496 were obtained from the GEO database to search differentially expressed circRNA (DECs), miRNAs (DEMis), and mRNAs (DEMs). GO and KEGG enrichment analyses, and protein-protein interaction (PPI) network construction were implemented to explore possible actions of DEMs. Hub genes were selected to establish circRNA-related competing endogenous RNA (ceRNA) networks.

Results: There were 1005 downregulated DECs, 21 upregulated and 21 downregulated DEMis, and 266 upregulated and 234 downregulated DEMs identified. The DEMs were significantly enriched in various PD-associated functions and pathways such as extracellular matrix organization, dopamine synthesis, PI3K-Akt, and calcium signaling pathways. Twenty-one hub genes were screened out, and a PD-related ceRNA regulatory network was constructed containing 31 circRNAs, one miRNA (miR-371a-3p), and one hub gene (KCNJ6).

Conclusion: We identified PD-related molecular markers and ceRNA regulatory networks, providing new directions for PD diagnosis and treatment.

Keywords: Dopaminergic neurons; Hub genes; Parkinson; ceRNA network; circRNA; s disease.

MeSH terms

  • Biomarkers* / metabolism
  • Computational Biology* / methods
  • Disease Progression*
  • Gene Expression Profiling
  • Gene Regulatory Networks*
  • Humans
  • MicroRNAs / genetics
  • Parkinson Disease* / genetics
  • Protein Interaction Maps
  • RNA, Circular / genetics
  • RNA, Messenger / genetics
  • RNA, Messenger / metabolism