Circular RNAs in Parkinson’s Disease: Reliable Biological Markers and Targets for Rehabilitation
Open accessPublished version of a preprint
Abstract
In clinical practice, the underlying pathogenesis of Parkinson's disease (PD) remains unknown. Circular RNAs (circRNAs) have good biological properties and can be used as biological marker. Rehabilitation as a third treatment alongside drug and surgery has been shown to be clinically effective, but biomarkers of rehabilitation efficiency at genetic level is still lacking. In this study, we identified differentially expressed circRNAs in peripheral blood exosomes between PD patients and health controls (HCs) and determined whether these circRNAs changed after rehabilitation, to explore the competing RNA networks and epigenetic mechanisms affected. We found that there were 558 upregulated and 609 downregulated circRNAs in PD patients compared to HCs, 3398 upregulated and 479 downregulated circRNAs in PD patients after rehabilitation compared to them before rehabilitation, along with 3721 upregulated and 635 downregulated circRNAs in PD patients after rehabilitation compared to HCs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that differentially expressed circRNAs may affect the stability of the cellular actin backbone and synaptic structure by influencing the aggregation of α-synuclein (a-syn). We selected two circRNAs overexpressed in PD patients for validation (hsa_circ_0001535 and hsa_circ_0000437); the results revealed that their expression levels were all reduced to varying degrees (p < 0.05) after rehabilitation. After network analysis, we believe that hsa_circ_0001535 may be related to the aggregation of a-syn, while hsa_circ_0000437 may act on hsa-let-7b-5p or hsa-let-7c-5p through sponge effect to cause inflammatory response. Our findings suggest that rehabilitation can mitigate the pathological process of PD by epigenetic means.
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Cites
Global quantification of mammalian gene expression control
Schwanhäusser, B., Busse, D., Li, N., Dittmar, G., Schuchhardt, J., Wolf, J., Chen, W., & Selbach, M. (2011) · Nature · doi:10.1038/nature10098 · Cited by 6,566 · see citing works
The diagnosis of Parkinson’s disease
Tolosa, E., Wenning, G., & Poewe, W. (2006) · The Lancet Neurology · doi:10.1016/s1474-4422(05)70285-4 · Cited by 902 · see citing works
The epigenetics of aging and neurodegeneration
Lardenoije, R., Iatrou, A., Kenis, G., Kompotis, K., Steinbusch, H. W. M., Mastroeni, D., Coleman, P., Lemere, C. A., Hof, P. R., van den Hove, D. L. A., et al. (2015) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2015.05.002 · Cited by 381 · see citing works
Więckowska-Gacek, A., Mietelska-Porowska, A., Wydrych, M., & Wojda, U. (2021) · Ageing Research Reviews · doi:10.1016/j.arr.2021.101397 · Cited by 343 · see citing works
Fisher, B. E., Li, Q., Nacca, A., Salem, G. J., Song, J., Yip, J., Hui, J. S., Jakowec, M. W., & Petzinger, G. M. (2013) · Neuroreport · doi:10.1097/wnr.0b013e328361dc13 · Cited by 247 · see citing works
Targeting Microglial α-Synuclein/TLRs/NF-kappaB/NLRP3 Inflammasome Axis in Parkinson’s Disease
Li, Y., Xia, Y., Yin, S., Wan, F., Hu, J., Kou, L., Sun, Y., Wu, J., Zhou, Q., Huang, J., et al. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.719807 · Cited by 230 · see citing works
Gene–environment interactions in Alzheimer disease: the emerging role of epigenetics
Migliore, L., & Coppedè, F. (2022) · Nature Reviews Neurology · doi:10.1038/s41582-022-00714-w · Cited by 217 · see citing works
p53 and mitochondrial dysfunction: novel insight of neurodegenerative diseases
Dai, C.-Q., Luo, T.-T., Luo, S.-C., Wang, J.-Q., Wang, S.-M., Bai, Y.-H., Yang, Y.-L., & Wang, Y.-Y. (2016) · Journal of Bioenergetics and Biomembranes · doi:10.1007/s10863-016-9669-5 · Cited by 93 · see citing works
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- Authors
- Duan, Y., Wang, Y., Liu, Y., Jin, Z., Liu, C., Yu, X., Chen, K., Meng, D., Xi, J., & Fang, B.
- Affiliations
- Capital Medical University (CN)
- Corresponding author
- Xi, Jianing
- Fang, Boyan
- ORCID
- Venue
- Molecular Neurobiology
- Published
- 2023-02-25
- Volume
- 60
- Issue
- 6
- Pages
- 3261-3276
- ISSN
- 0893-7648 (ISSN-L)
- 1559-1182
- OpenAlex
- W4321996948
- Cited by
- 17
- References
- 8
- Citations by year
- 2026: 1 · 2025: 7 · 2024: 5 · 2023: 3
- FWCI
- 1.42
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Molecular Neurobiology (publishedVersion)
- Research Square (acceptedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Science and Technology Development Fund (2019-023, 2020R-001, 2020-069, 2021-011)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Circular RNAs in diseases
- Health Sciences › Medicine › Neurology › Parkinson's Disease Mechanisms and Treatments
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Extracellular vesicles in disease
- Keywords
- Parkinson's disease, circular RNA, rehabilitation, blood exosomes, biomarkers, alpha-synuclein aggregation, competing endogenous RNA network, epigenetic regulation, actin cytoskeleton, synaptic structure, inflammation
- MeSH terms
- RNA, Circular, Humans, Parkinson Disease, RNA, Biomarkers, MicroRNAs, alpha-Synuclein
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