Evidence map›Paper›PMID 36927756›Full record

ArticleNPJ Parkinson's disease2023

MAPKAPK2, a potential dynamic network biomarker of α-synuclein prior to its aggregation in PD patients.

Zhenggang Zhong, Jiabao Li, Jiayuan Zhong, Yilin Huang, Jiaqi Hu, Piao Zhang, Baowen Zhang, Yabin Jin, Wei Luo, Rui Liu and 2 more

Open access · goldFull text read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ Parkinson's disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 27% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Identification of dynamic network biomarkerMolecular therapy. Oncology · 2025
    Article
  3. Article
  4. Article
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

12 authors at 4 institutions in 1 country.

Zhenggang ZhongGuangdong Key Laboratory of Fermentation and Enzyme Engineering, School of Biology and Biological Engineering, South China University of Technology, Guangzhou, Guangdong, China.
Jiabao LiGuangdong Key Laboratory of Fermentation and Enzyme Engineering, School of Biology and Biological Engineering, South China University of Technology, Guangzhou, Guangdong, China.
Jiayuan ZhongSchool of Mathematics, South China University of Technology, Guangzhou, Guangdong, China.
Yilin HuangGuangdong Key Laboratory of Fermentation and Enzyme Engineering, School of Biology and Biological Engineering, South China University of Technology, Guangzhou, Guangdong, China.
Jiaqi HuGuangdong Key Laboratory of Fermentation and Enzyme Engineering, School of Biology and Biological Engineering, South China University of Technology, Guangzhou, Guangdong, China.
Piao ZhangDepartment of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Baowen ZhangGuangdong Key Laboratory of Fermentation and Enzyme Engineering, School of Biology and Biological Engineering, South China University of Technology, Guangzhou, Guangdong, China.
Yabin JinThe First People's Hospital of Foshan, Sun Yat-sen University, Foshan, China.
Wei LuoThe First People's Hospital of Foshan, Sun Yat-sen University, Foshan, China. luowei_421@163.com.
Rui LiuSchool of Mathematics, South China University of Technology, Guangzhou, Guangdong, China. scliurui@scut.edu.cn.ORCID http://orcid.org/0000-0002-4547-8695
Yuhu ZhangDepartment of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China. yhzhangsd@126.com.ORCID http://orcid.org/0000-0003-3492-4669
Fei LingGuangdong Key Laboratory of Fermentation and Enzyme Engineering, School of Biology and Biological Engineering, South China University of Technology, Guangzhou, Guangdong, China. fling@scut.edu.cn.
South China University of Technology · CNGuangdong Academy of Medical Sciences · CNSun Yat-sen University · CNGuangdong University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

One of the important pathological features of Parkinson's disease (PD) is the pathological aggregation of α-synuclein (α-Syn) in the substantia nigra. Preventing the aggregation of α-Syn has become a potential strategy for treating PD. However, the molecular mechanism of α-Syn aggregation is unclear. In this study, using the dynamic network biomarker (DNB) method, we first identified the critical time point when α-Syn undergoes pathological aggregation based on a SH-SY5Y cell model and found that DNB genes encode transcription factors that regulated target genes that were differentially expressed. Interestingly, we found that these DNB genes and their neighbouring genes were significantly enriched in the cellular senescence pathway and thus proposed that the DNB genes HSF1 and MAPKAPK2 regulate the expression of the neighbouring gene SERPINE1. Notably, in Gene Expression Omnibus (GEO) data obtained from substantia nigra, prefrontal cortex and peripheral blood samples, the expression level of MAPKAPK2 was significantly higher in PD patients than in healthy people, suggesting that MAPKAPK2 has potential as an early diagnostic biomarker of diseases related to pathological aggregation of α-Syn, such as PD. These findings provide new insights into the mechanisms underlying the pathological aggregation of α-Syn.

Identifiers

PMID36927756
PMCPMC10020541
OpenAlexW4327587732

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