Evidence map›Paper›PMID 36840847›Full record

ArticleMolecular neurobiology2023

Circular RNAs in Parkinson's Disease: Reliable Biological Markers and Targets for Rehabilitation.

Yinan Duan, Yixuan Wang, Yonghong Liu, Zhaohui Jin, Cui Liu, Xin Yu, Keke Chen, Detao Meng, Jianing Xi, Boyan Fang

Abstract read
PubMed Publisher
In one paragraph

Article in Molecular neurobiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.3field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 16 citations in OpenAlex.

  1. Review
  2. Circular RNA PTPN4 Contributes to Blood-Brain Barrier Disruption during Early Epileptogenesis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
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  4. Review
  5. Article
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  8. [Resveratrol protects dopaminergic neurons in a mouse model of Parkinson's disease by regulating the gut-brain axisNan fang yi ke da xue xue bao = Journal of Southern Medical University · 2024
    Article
  9. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 1 institution in 1 country.

Yinan Duan *Capital Medical University School of Beijing Rehabilitation Medicine, Capital Medical University, Beijing, China.
Yixuan Wang *Parkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China.
Yonghong LiuParkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China.
Zhaohui JinParkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China.
Cui LiuParkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China.
Xin YuCapital Medical University School of Beijing Rehabilitation Medicine, Capital Medical University, Beijing, China.
Keke ChenCapital Medical University School of Beijing Rehabilitation Medicine, Capital Medical University, Beijing, China.
Detao MengParkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China.
Jianing XiParkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China. xijn888@sina.com.
Boyan FangParkinson Medical Center, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China. fangboyanv@ccmu.edu.cn.ORCID http://orcid.org/0000-0002-9935-433X
Capital Medical University · CN

Funding

Science and Technology Development Fund 2019-023Science and Technology Development Fund 2020-069Science and Technology Development Fund 2020R-001Science and Technology Development Fund 2021-011
6 · The paper itself

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.

Indexed as

MicroRNAsParkinson Diseasealpha-SynucleinBiomarkersHumansRNARNA, Circularalpha-SynucleinBiomarkersMicroRNAsRNARNA, CircularBiomarkerCircular RNAsEpigeneticsParkinson’s diseaseRehabilitationα-Synuclein

Identifiers

PMID36840847
OpenAlexW4321996948

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.