Unveiling new therapeutic horizons in rheumatoid arthritis: an In-depth exploration of circular RNAs derived from plasma exosomes
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 pati...
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| Format: | Article |
| Language: | English |
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BMC
2025-01-01
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| Series: | Journal of Orthopaedic Surgery and Research |
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| Online Access: | https://doi.org/10.1186/s13018-025-05494-9 |
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| author | Guoqing Li Hongyi Chen Jiacheng Shen Yimin Ding Jingqiong Chen Yongbin Zhang Mingrui Tang Nan Xu Yuxuan Fang |
| author_facet | Guoqing Li Hongyi Chen Jiacheng Shen Yimin Ding Jingqiong Chen Yongbin Zhang Mingrui Tang Nan Xu Yuxuan Fang |
| author_sort | Guoqing Li |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-acf0b12b4b7843eda6ef45859aeaa9e1 |
| institution | Kabale University |
| issn | 1749-799X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Orthopaedic Surgery and Research |
| spelling | doaj-art-acf0b12b4b7843eda6ef45859aeaa9e12025-02-02T12:34:10ZengBMCJournal of Orthopaedic Surgery and Research1749-799X2025-01-0120111310.1186/s13018-025-05494-9Unveiling new therapeutic horizons in rheumatoid arthritis: an In-depth exploration of circular RNAs derived from plasma exosomesGuoqing Li0Hongyi Chen1Jiacheng Shen2Yimin Ding3Jingqiong Chen4Yongbin Zhang5Mingrui Tang6Nan Xu7Yuxuan Fang8Department of Rheumatology and Immunology, Affiliated Hospital of Yangzhou University, Yangzhou UniversityDepartment of Rheumatology and Immunology, Affiliated Hospital of Yangzhou University, Yangzhou UniversityDepartment of Rheumatology and Immunology, Affiliated Hospital of Yangzhou University, Yangzhou UniversityDepartment of Rheumatology and Immunology, Affiliated Hospital of Yangzhou University, Yangzhou UniversityDepartment of Rheumatology and Immunology, Affiliated Hospital of Yangzhou University, Yangzhou UniversityDepartment of Rheumatology and Immunology, Affiliated Hospital of Yangzhou University, Yangzhou UniversityDepartment of Rheumatology and Immunology, Affiliated Hospital of Yangzhou University, Yangzhou UniversityDepartment of Rheumatology and Immunology, Affiliated Hospital of Yangzhou University, Yangzhou UniversityDepartment of Rheumatology and Immunology, Affiliated Hospital of Yangzhou University, Yangzhou UniversityAbstract 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.https://doi.org/10.1186/s13018-025-05494-9Rheumatoid arthritisTumor necrosis factor inhibitorscircRNAPlasma exosomesMachine learning |
| spellingShingle | Guoqing Li Hongyi Chen Jiacheng Shen Yimin Ding Jingqiong Chen Yongbin Zhang Mingrui Tang Nan Xu Yuxuan Fang Unveiling new therapeutic horizons in rheumatoid arthritis: an In-depth exploration of circular RNAs derived from plasma exosomes Journal of Orthopaedic Surgery and Research Rheumatoid arthritis Tumor necrosis factor inhibitors circRNA Plasma exosomes Machine learning |
| title | Unveiling new therapeutic horizons in rheumatoid arthritis: an In-depth exploration of circular RNAs derived from plasma exosomes |
| title_full | Unveiling new therapeutic horizons in rheumatoid arthritis: an In-depth exploration of circular RNAs derived from plasma exosomes |
| title_fullStr | Unveiling new therapeutic horizons in rheumatoid arthritis: an In-depth exploration of circular RNAs derived from plasma exosomes |
| title_full_unstemmed | Unveiling new therapeutic horizons in rheumatoid arthritis: an In-depth exploration of circular RNAs derived from plasma exosomes |
| title_short | Unveiling new therapeutic horizons in rheumatoid arthritis: an In-depth exploration of circular RNAs derived from plasma exosomes |
| title_sort | unveiling new therapeutic horizons in rheumatoid arthritis an in depth exploration of circular rnas derived from plasma exosomes |
| topic | Rheumatoid arthritis Tumor necrosis factor inhibitors circRNA Plasma exosomes Machine learning |
| url | https://doi.org/10.1186/s13018-025-05494-9 |
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