Evidence map›Paper›PMID 32536974›Full record

ArticleBioData mining2020

The accelerated aging model reveals critical mechanisms of late-onset Parkinson's disease.

Shiyan Li, Hongxin Liu, Shiyu Bian, Xianzheng Sha, Yixue Li, Yin Wang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BioData mining, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
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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

6 authors.

Shiyan LiDepartment of Biomedical Engineering, School of Fundamental Sciences, China Medical University, Shenyang, 110122 Liaoning Province China.
Hongxin LiuDepartment of Biomedical Engineering, School of Fundamental Sciences, China Medical University, Shenyang, 110122 Liaoning Province China.
Shiyu BianChina Medical University, The Queen's University of Belfast Joint College, China Medical University, Shenyang, 110122 Liaoning Province China.
Xianzheng ShaDepartment of Biomedical Engineering, School of Fundamental Sciences, China Medical University, Shenyang, 110122 Liaoning Province China.
Yixue LiBio-Med Big Data Center, Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Science, Shanghai, 200031 China.
Yin WangDepartment of Biomedical Engineering, School of Fundamental Sciences, China Medical University, Shenyang, 110122 Liaoning Province China.ORCID 0000-0003-3120-8579

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLate-onset Parkinson's disease (LOPD) is a common neurodegenerative disorder and lacks disease-modifying treatments, attracting major attentions as the aggravating trend of aging population. There were numerous evidences supported that accelerated aging was the primary risk factor for LOPD, thus pointed out that the mechanisms of PD should be revealed thoroughly based on aging acceleration. However, how PD was triggered by accelerated aging remained unclear and the systematic prediction model was needed to study the mechanisms of PD.

resultsIn this paper, an improved PD predictor was presented by comparing with the normal aging process, and both aging and PD markers were identified herein using machine learning methods. Based on the aging scores, the aging acceleration network was constructed thereby, where the enrichment analysis shed light on key characteristics of LOPD. As a result, dysregulated energy metabolisms, the cell apoptosis, neuroinflammation and the ion imbalances were identified as crucial factors linking accelerated aging and PD coordinately, along with dysfunctions in the immune system.

conclusionsIn short, mechanisms between aging and LOPD were integrated by our computational pipeline.

Indexed as

Aging accelerationLate-onset Parkinson’s diseaseNetwork analysis

Identifiers

PMID32536974
PMCPMC7288517

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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.