ArticleJournal of orthopaedic surgery and research2025
Unveiling new therapeutic horizons in rheumatoid arthritis: an In-depth exploration of circular RNAs derived from plasma exosomes.
Article in Journal of orthopaedic surgery and research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- The effect of mobilization with movement on pain, joint distance, effusion area, and inflammation in rheumatoid arthritis: a double-blind randomized controlled clinical trial.Journal of orthopaedic surgery and research · 2025Trial
- Transcriptomics and AI-driven approaches to the diagnosis and treatment of rheumatoid arthritis.Frontiers in immunology · 2026Review
- Brain-derived extracellular vesicles circUsp32 polarized macrophages causing acute kidney injury after traumatic brain injury.Science advances · 2025Article
- Current application, possibilities, and challenges of artificial intelligence in the management of rheumatoid arthritis, axial spondyloarthritis, and psoriatic arthritis.Therapeutic advances in musculoskeletal disease · 2025Review
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Authors and funding
9 authors.
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Abstract
Rheumatoid arthritis (RA), a chronic inflammatory joint disease causing permanent disability, involves exosomes, nanosized mammalian extracellular particles. Circular RNA (circRNA) serves as a biomarker in RA blood samples. This research screened differentially expressed circRNAs in RA patient plasma exosomes for novel diagnostic biomarkers. In this study, samples of RA patients with insufficient response to methotrexate (MTX-IR), combined use of tumor necrosis factor inhibitors (TNFi) were followed up for half a year, and 56 circRNA samples of self-test data were stratified into training, testing, and external validation cohorts according to whether American College of Rheumatology 20% improvement criteria (ACR20) was achieved. A diagnostic xgboost model was developed using common hub genes identified by random forest and least absolute shrinkage and selection operator (LASSO), with intersection genes derived from overlapping machine learning-selected genes. Diagnostic performance evaluated via receiver operating characteristic (ROC) curves using pROC for area under the curve (AUC). Optimal LASSO model with 4 circRNAs determined, with AUC > 0.6 for key genes. The model validation performed well on the test set, but not significantly on the validation set. Then, circRNA screening was performed in combination with clinical data, and cross-validation identified hsa-circ0002715, hsa-circ0001946, hsa-circ0000836, and rheumatoid factor (RF) as key genes, among which hsa-circ0002715 and hsa-circ0001946 were emphasized as key markers on the training set. In addition, the morphology and size of exosomes and the expression of CD9 and CD81 verified the successful extraction of exosomes. The qPCR analysis of plasma exosomes in TNFi patients found that the expression of hsa-circ0002715 was higher than that in patients who didn't reach ACR20, and the expression of hsa-circ0001946 was lower than that in patients who didn't reach ACR20. The above studies suggested that hsa-circ0002715 and hsa-circ0001946 may become markers for predicting MTX-IR RA patients and TNFi precision treatment.
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