ArticleJournal of orthopaedic surgery and research2018
Transcriptome analyses identify key genes and potential mechanisms in a rat model of osteoarthritis.
Article in Journal of orthopaedic surgery and research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 15 citations in OpenAlex.
- Methylation Landscapes of Cartilage in Hip Osteoarthritis.Genetics research · 2026Article
- Senescence-Driven Inflammatory and Trophic Microenvironment Imprints Mesenchymal Stromal/Stem Cells in Osteoarthritic Patients.Biomedicines · 2023Article
- RNA profiling of human dorsal root ganglia reveals sex differences in mechanisms promoting neuropathic pain.Brain : a journal of neurology · 2023Article
- Deer antler extract potentially facilitates xiphoid cartilage growth and regeneration and prevents inflammatory susceptibility by regulating multiple functional genes.Journal of orthopaedic surgery and research · 2021Article
- Construction and Validation of an Autophagy-Related Prognostic Model for Osteosarcoma Patients.Journal of oncology · 2021Article
- Sex Differences in Osteoarthritis Pathogenesis: A Comprehensive Study Based on Bioinformatics.Medical science monitor : international medical journal of experimental and clinical research · 2020Article
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundOsteoarthritis (OA) is one of the most common degenerative diseases of the joints worldwide, but still the pathogenesis of OA is largely unknown. The purpose of our study is to clarify key candidate genes and relevant signaling pathways in a surgical-induced OA rat model.
methodsThe microarray raw data of GSE8077 was downloaded from GEO datasets. GeoDiver were employed to screen differentially-expressed genes (DEGs). Enrichment analyses of DEGs were performed using Metascape. Construction of protein-protein interaction (PPI) network and identification of key genes were conducted using STRING, Cytoscape v3.6.0, and Centiscape2.2. Furthermore, miRDB and Cytoscape v3.6.0 were used for visualization of miRNA-mRNA regulatory network. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis for predicted miRNAs was undertaken using DIANA-miRPath v3.0.
resultsSeveral DEGs (188 in comparison between OA and sham-operated group and 160 in comparison between OA and contralateral group) were identified. DEGs mainly enriched in vasculature development, regulation of cell migration, response to growth factor (Gene ontology), and ECM-receptor interaction (KEGG). Two comparison cohorts shared 79 intersection genes, and of these, Ccl2, Col4a1, Col1a1, Aldh1a3, and Itga8 were defined as the hub genes. Predicted miRNAs of seven DEGs from sub-networks mainly enriched in MAPK signaling pathway.
conclusionThe current study shows that some key genes and pathways, such as Ccl2, Col4a1, Col1a1, Aldh1a3, Itga8, ECM-receptor interaction, and MAPK signaling pathway may be associated with OA progression and act as potential biomarkers and therapeutic targets for OA.
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