Identifying the NEAT1/miR-26b-5p/S100A2 axis as a regulator in Parkinson's disease based on the ferroptosis-related genes

Taole Li; Jifeng Guo

doi:10.1371/journal.pone.0316179

Identifying the NEAT1/miR-26b-5p/S100A2 axis as a regulator in Parkinson's disease based on the ferroptosis-related genes

PLoS One. 2024 Dec 31;19(12):e0316179. doi: 10.1371/journal.pone.0316179. eCollection 2024.

Authors

Taole Li¹, Jifeng Guo^{1

2

3

4

5}

Affiliations

¹ Department of Neurology, Xiangya Hospital, Central South University, Changsha, China.
² Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Centre for Medical Genetics, Central South University, Changsha, China.
³ Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China.
⁴ National Clinical Research Centre for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.
⁵ Hunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Changsha, China.

Abstract

Objectives: Parkinson's disease (PD) is a complex neurodegenerative disease with unclear pathogenesis. Some recent studies have shown that there is a close relationship between PD and ferroptosis. We aimed to identify the ferroptosis-related genes (FRGs) and construct competing endogenous RNA (ceRNA) networks to further assess the pathogenesis of PD.

Methods: Expression of 97 substantia nigra (SN) samples were obtained and intersected with FRGs. Bioinformatics analysis, including the gene set enrichment analysis (GSEA), consensus cluster analysis, weight gene co-expression network analysis (WGCNA), and machine learning algorithms, were employed to assess the feasible differentially expressed genes (DEGs). Characteristic signature genes were used to create novel diagnostic models and construct competing endogenous RNA (ceRNA) regulatory network for PD, which were further verified by in vitro experiments and single-cell RNA sequencing (scRNA-seq).

Results: A total of 453 DEGs were identified and 11 FRGs were selected. We sorted the entire PD cohort into two subtypes based on the FRGs and obtained 67 hub genes. According to the five machine algorithms, 4 features (S100A2, GNGT1, NEUROD4, FCN2) were screened and used to create a PD diagnostic model. Corresponding miRNAs and lncRNAs were predicted to construct a ceRNA network. The scRNA-seq and experimental results showed that the signature model had a certain diagnostic effect and lncRNA NEAT1 might regulate the progression of ferroptosis in PD via the NEAT1/miR-26b-5p/S100A2 axis.

Conclusion: The diagnostic signatures based on the four FRGs had certain diagnostic and individual effects. NEAT1/miR-26b-5p/S100A2 axis is associated with ferroptosis in the pathogenesis of PD. Our findings provide new solutions for treating PD.

Copyright: © 2024 Li, Guo. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

MeSH terms

Computational Biology / methods
Female
Ferroptosis* / genetics
Gene Expression Profiling
Gene Regulatory Networks*
Humans
Male
MicroRNAs* / genetics
Parkinson Disease* / genetics
Parkinson Disease* / metabolism
Parkinson Disease* / pathology
RNA, Long Noncoding* / genetics

Substances

MicroRNAs
MIRN26 microRNA, human
RNA, Long Noncoding
NEAT1 long non-coding RNA, human

Grants and funding

This research was funded by the National Natural Science Foundation of China (Grant No. 81873785) and the Technology Major Project of Hunan Provincial Science and Technology Department (Grant No. 2021SK1010). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.