Evidence map›Paper›PMID 30483788›Full record

ArticleMolecular medicine reports2019

Microarray analysis of the molecular mechanisms associated with age and body mass index in human meniscal injury.

Peiyan Huang, Jun Gu, Junguo Wu, Lei Geng, Yang Hong, Siqun Wang, Minghai Wang

Erratum issuedOpen access · hybridAbstract read
In one paragraph

Article in Molecular medicine reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 23% 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, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Identification of Pivotal Genes and Pathways in Osteoarthritic Degenerative Meniscal Lesions via Bioinformatics Analysis of the GSE52042 Dataset.Medical science monitor : international medical journal of experimental and clinical research · 2019
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Peiyan HuangDepartment of Orthopedic Surgery, Shanghai Fifth People's Hospital Affiliated to Fudan University, Shanghai 200240, P.R. China.
Jun GuDepartment of Orthopedic Surgery, Shanghai Fifth People's Hospital Affiliated to Fudan University, Shanghai 200240, P.R. China.
Junguo WuDepartment of Orthopedic Surgery, Shanghai Fifth People's Hospital Affiliated to Fudan University, Shanghai 200240, P.R. China.
Lei GengDepartment of Orthopedic Surgery, Shanghai Fifth People's Hospital Affiliated to Fudan University, Shanghai 200240, P.R. China.
Yang HongDepartment of Orthopedic Surgery, Shanghai Fifth People's Hospital Affiliated to Fudan University, Shanghai 200240, P.R. China.
Siqun WangDepartment of Orthopedic Surgery, Shanghai Fifth People's Hospital Affiliated to Fudan University, Shanghai 200240, P.R. China.
Minghai WangDepartment of Orthopedic Surgery, Shanghai Fifth People's Hospital Affiliated to Fudan University, Shanghai 200240, P.R. China.
Fudan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of the present study was to identify genes and functional pathways associated with meniscal injuries affected by age or body mass index (BMI) using microarray analysis. The GSE45233 gene expression dataset with 12 injured meniscus samples associated with age and BMI and GSE66635 dataset with 12 injured and 12 normal meniscus samples were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified based on age or BMI in GSE45233. DEGs between injured and normal meniscus samples in GSE66635 were also identified. Common DEGs between GSE45233 and GSE66635 were identified as feature genes associated with age or BMI, followed by protein‑protein interaction (PPI) network and functional pathway enrichment analyses for the feature genes. Finally, the GSE51588 genome‑wide expression profile was then downloaded from the GEO database to validate the results. A total of 1,328 DEGs were identified. Of these, 28 age‑associated and 20 BMI‑associated meniscal injury genes were obtained. B‑cell lymphoma‑2 (Bcl‑2) and matrix metalloproteinase‑14 were identified as hub genes in the PPI networks. Functional pathway enrichment analysis revealed that vascular endothelial growth factor A (VEGFA), transferrin (TF) and Bcl‑2 were involved in the hypoxia‑inducible factor 1 signaling pathway. TF was involved in the mineral absorption function pathway associated with BMI. Additionally, TF and VEGFA were identified to be overlapping candidate genes of GSE45233 and GSE66635, and DEGs in GSE51588. Therefore, VEGFA, TF, and Bcl‑2 may be important genes for human meniscal injuries. Additional evaluations of these results are required.

Indexed as

AdultBody Mass IndexFemaleGene Expression ProfilingGene OntologyGene Regulatory NetworksHumansMaleMatrix MetalloproteinasesMeniscusMicroarray AnalysisProtein Interaction MapsSignal TransductionTibial Meniscus InjuriesVascular Endothelial Growth Factor AMatrix MetalloproteinasesVascular Endothelial Growth Factor Aagebody mass indexdifferentially expressed genesfunctional enrichment analysismeniscal injuryprotein-protein interaction network

Identifiers

PMID30483788
PMCPMC6297773
OpenAlexW2988714155

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LicenceCC BY-NC-ND
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Registered trials

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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.