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- Title
铜死亡调节因子在骨关节炎诊断及亚分型中的作用.
- Authors
熊 波; 王 斌; 刘金富; 陆冠宇; 陈 财; 黄 悦; 陈莉华
- Abstract
BACKGROUND: Synovium plays an important role in the development of osteoarthritis, and cuproptosis is a new type of programmed cell death recently discovered, up to now, there is no research on the mechanism of cuproptosis gene in osteoarthritis from synovial angle. OBJECTIVE: The synovial membrane was used as the entry point to explore the potential mechanism of the development of osteoarthritis from the perspective of cuproptosis. METHODS: The coincident osteoarthritis related chips were retrieved through Gene Expression Omnibus (GEO) database and standardized. Cuproptosis related genes were extracted and quantified based on the gene expression matrix after treatment. Random Forest model, Support Vector Machines model, Machine learning and Nomogram Model were used to construct disease prediction model to predict the risk of osteoarthritis. Then, consensus clustering algorithm, principal component analysis, single sample gene set enrichment analysis and immune infiltration were used to analyze the correlation of cuproptosis molecular subtypes with immune microenvironment and inflammatory factors. RESULTS AND CONCLUSION: (1) A risk prediction model based on cuproptosis characteristic gene was established for the first time. The disease prediction model constructed by three cuproptosis characteristic genes (DBT, LIPT1, FDX1) could predict the risk of osteoarthritis. (2) It is found for the first time that patients with osteoarthritis can be classified into two distinct subtypes of cuproptosis molecule (cluster A and cluster B). Cluster B is highly correlated with the imbalance of Th1/Th2 cell ratio, and has higher expression levels of interleukin-2, interleukin-4, and interleukin-5.
- Subjects
APOPTOSIS; SYNOVIAL membranes; GENE expression; SUPPORT vector machines; PRINCIPAL components analysis; MACHINE learning
- Publication
Chinese Journal of Tissue Engineering Research / Zhongguo Zuzhi Gongcheng Yanjiu, 2023, Vol 27, Issue 34, p5530
- ISSN
2095-4344
- Publication type
Article
- DOI
10.12307/2023.702