ArticleNaunyn-Schmiedeberg's archives of pharmacology2026
Deciphering the mechanisms of resveratrol in knee osteoarthritis treatment: insights from bioinformatics and experimental validation.
Article in Naunyn-Schmiedeberg's archives of pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- Pulmonary embolism associated with CRBN-targeting immunomodulatory drugs: a FAERS-based pharmacovigilance and mechanistic analysis.Journal of thrombosis and thrombolysis · 2026Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Knee osteoarthritis (KOA) is the most prevalent chronic joint disorder in orthopedics, with its underlying pathogenic genes and effective treatment methods remaining unclear. Resveratrol (RES), a potent bioactive natural polyphenol, has been shown to effectively alleviate KOA; however, its complex regulatory mechanisms require further investigation. This research seeks to clarify the molecular mechanisms by which RES contributes to the treatment of KOA, utilizing a blend of bioinformatics approaches and experimental validation. First, gene expression profiles related to KOA were obtained from the GEO database. Subsequently, differential gene analysis was conducted on the samples, and modular genes linked to KOA were extracted through the application of a weighted gene co-expression network. The LASSO algorithm was utilized to identify crucial pathogenic genes in KOA, which were later confirmed using clinical samples. Targets for RES were sourced from traditional Chinese medicine databases, and the therapeutic targets for KOA treatment were determined by finding the intersection of these sources. An enrichment analysis was carried out based on the therapeutic targets identified. Molecular docking studies were conducted to further assess the binding affinity of key therapeutic genes with RES. Lastly, animal experiments were implemented to substantiate the molecular mechanisms by which RES acts in the treatment of KOA. We identified 460 module genes and 10 key predictive genes through LASSO analysis. The findings from the enrichment analysis concerning potential therapeutic targets for RES in the treatment of KOA reveal that the significant genes implicated include VEGFA, IL6, MAPK3, IL1B, CASP3, and AKT1. Subsequent validation with clinical samples revealed that IL6, MAPK3, IL1B, CASP3, and AKT1 were significantly elevated during the progression of KOA, while VEGFA was markedly reduced in the context of KOA. The outcomes of the GO and KEGG analyses suggest that the primary biological processes implicated encompass apoptosis, the FoxO signaling pathway, the IL-17 signaling pathway, cellular senescence, and the NF-κB signaling pathway. The findings from the immune infiltration analysis indicate that resting CD4 memory T cells, memory B cells, resting mast cells, eosinophils, and activated mast cells may have important functions in the immune mechanisms related to KOA. The results of animal experiments demonstrate that RES effectively inhibits the expression of inflammatory factors such as IL-6, MAPK3, IL-1β, CASP3, and AKT1 during the progression of KOA, promotes the expression of VEGFA, and concurrently suppresses the FoxO signaling pathway and the IL-17 signaling pathway, thereby reducing cartilage damage induced by MIA and delaying the progression of KOA. In summary, RES can regulate the expression of genes including VEGFA, IL-6, MAPK3, IL-1β, CASP3, and AKT1, inhibit the FoxO signaling pathway and the IL-17 signaling pathway, alleviate cartilage damage induced by MIA, and delay the progression of KOA.
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Registered trials
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.