ArticleOsteoarthritis and cartilage open2022
Differential gene co-expression network analyses reveal novel molecules associated with transcriptional dysregulation of key biological processes in osteoarthritis knee cartilage.
Article in Osteoarthritis and cartilage open, 2022. 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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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.
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Who cites it
3 citing papers in PubMed, 3 citations in OpenAlex.
- Integrated analysis identifies conserved transcription factors TCF12, E2F1, and TEAD4 with diagnostic and therapeutic value in osteoarthritis subchondral bone.Genes & genomics · 2026Article
- Identification of diagnostic biomarkers for osteoarthritis through bioinformatics and machine learning.Heliyon · 2024Article
- Pleiotropic Roles of a KEAP1-Associated Deubiquitinase, OTUD1.Antioxidants (Basel, Switzerland) · 2023Review
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: To compare co-expression networks of normal and osteoarthritis knee cartilage to uncover molecules associated with the transcriptional misregulation compromising biological processes (BPs) critical for cartilage homeostasis. Design: Normal and osteoarthritis human knee cartilage RNA-seq GSE114007 dataset was obtained from the Gene Expression Omnibus database. Partial Correlation and Information Theory (PCIT) algorithm was used to build co-expression networks containing all nodes connecting to at least one differentially expressed gene (DEG) in normal and osteoarthritis networks. Hub and hub centrality genes were used to perform functional enrichment analysis. Enriched BPs known to be associated with both healthy and diseased cartilage were compared in depth. Results: Differential co-expression network analyses allowed the identification of Conclusion: Differential gene co-expression analysis allowed the identification of novel and high priority therapeutic candidate genes that may drive modifications in the transcriptional "status" of cartilage in osteoarthritis.
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