ArticleMolecular medicine reports2019
Microarray analysis of the molecular mechanisms associated with age and body mass index in human meniscal injury.
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.
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Who cites it
4 citing papers in PubMed, 7 citations in OpenAlex.
- Identifying Key Genes to the Early Diagnosis of Inflammatory Bowel Disease by Integrating Analysis at the Blood and Tissue Levels.Gastroenterology research · 2023Article
- Integrated Analysis of lncRNA and mRNA Expression Profiles Indicates Age-Related Changes in Meniscus.Frontiers in cell and developmental biology · 2022Article
- Identification and validation of pivotal genes related to age-related meniscus degeneration based on gene expression profiling analysis and in vivo and in vitro models detection.BMC medical genomics · 2021Article
- 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 · 2019Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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