ArticleJournal of orthopaedic surgery and research2020
Bioinformatics analysis of differentially expressed genes in subchondral bone in early experimental osteoarthritis using microarray data.
Article in Journal of orthopaedic surgery and research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Spatial transcriptomics reveals microenvironmental heterogeneity in osteoarthritic subchondral bone.Nature communications · 2026Article
- Genetic and epidemiologic assessment of mandibular cortical indices and bone mineral density in peripubertal children: the Generation R study.Clinical oral investigations · 2025Article
- Cross-Tissue Analysis Using Machine Learning to Identify Novel Biomarkers for Knee Osteoarthritis.Computational and mathematical methods in medicine · 2022Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundOsteoarthritis (OA) is the most common arthritic disease in humans, affecting the majority of individuals over 65 years of age. The aim of this study is to identify the gene expression profile specific to subchondral bone in OA by comparing the different expression profiles in experimental and sham-operation groups.
methodsGene expression profile GSE30322 was downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were obtained by limma package. And Database for Annotation, Visualization and Integrated Discovery (DAVID) databases were further used to identify the potential gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Furthermore, a protein-protein interaction (PPI) network was constructed and significant modules were extracted.
resultsTotally, 588 DEGs were identified including 199 upregulated DEGs and 389 downregulated DEGs screened in OA and sham-operation. GO showed that DEGs were significantly enhanced for ribosomal subunit export from nucleus and molting cycle. KEGG pathway analysis revealed that target genes were enriched in thiamine metabolism.
conclusionThese key candidate DEGs that affect the progression of OA, and these genes might serve as potential therapeutic targets for OA.
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