Evidence map›Paper›PMID 27349437›Full record

ArticleMolecular neurobiology2017

Network and Pathway-Based Analyses of Genes Associated with Parkinson's Disease.

Yanshi Hu, Zhenhua Pan, Ying Hu, Lei Zhang, Ju Wang

Abstract read
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In one paragraph

Article in Molecular neurobiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
3.0field-weighted citation impact, top 9% 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

28 citing papers in PubMed, 1 synthesis or guideline pooled it, 45 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Yanshi HuSchool of Biomedical Engineering, Tianjin Medical University, Tianjin, 300070, China.
Zhenhua PanSchool of Biomedical Engineering, Tianjin Medical University, Tianjin, 300070, China.
Ying HuSchool of Biomedical Engineering, Tianjin Medical University, Tianjin, 300070, China.
Lei ZhangSchool of Computer Science and Technology, Tianjin University, Tianjin, 300072, China. lzhang@tju.edu.cn.
Ju WangSchool of Biomedical Engineering, Tianjin Medical University, Tianjin, 300070, China. wangju@tmu.edu.cn.ORCID 0000-0002-6514-0923
Tianjin Medical University · CNTianjin University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Parkinson's disease (PD) is a major neurodegenerative disease influenced by both genetic and environmental factors. Although previous studies have provided insights into the significant impacts of genetic factors on PD, the molecular mechanism underlying PD remains largely unclear. Under such situation, a comprehensive analysis focusing on biological function and interactions of PD-related genes will provide us valuable information to understand the pathogenesis of PD. In the current study, by reviewing the literatures deposited in PUBMED, we identified 242 genes genetically associated with PD, referred to as PD-related genes gene set (PDgset). Functional analysis revealed that biological processes and biochemical pathways related to neurodevelopment, metabolism, and immune system were enriched in PDgset. Then, pathway crosstalk analysis indicated that the enriched pathways could be grouped into two modules, with one module consisted of pathways mainly involved in neuronal signaling and another in immune response. Further, based on a global human interactome, we found that PDgset tended to have more moderate degree compared with cancer-related genes. Moreover, PD-specific molecular network was inferred using Steiner minimal tree algorithm and some potential related genes associated with PD were identified. In summary, by using network- and pathway-based methods to explore pathogenetic mechanism underlying PD, results from our work may have important implications for understanding the molecular mechanism underlying PD. Also, the framework proposed in our current work can be used to infer pathological molecular network and genes related to a specific disease.

Indexed as

Gene Regulatory NetworksGenetic Association StudiesGenetic Predisposition to DiseaseDatabases, GeneticHumansParkinson DiseaseSignal TransductionFunctional enrichment analysisNetwork analysisParkinson’s diseasePathway crosstalk

Identifiers

PMID27349437
OpenAlexW2463677272

What OpenQuestion holds

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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.