Chinese Journal of Tissue Engineering Research ›› 2023, Vol. 27 ›› Issue (34): 5530-5537.doi: 10.12307/2023.702

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Role of cuproptosis regulator in diagnosis and subtype of osteoarthritis

Xiong Bo1, Wang Bin2, Liu Jinfu1, Lu Guanyu1, Chen Cai1, Huang Yue1, Chen Lihua1   

  1. 1Graduate School of Guangxi University of Chinese Medicine, Nanning 530299, Guangxi Zhuang Autonomous Region, China; 2First Affiliated Hospital of Guangxi University of Chinese Medicine, Nanning 530023, Guangxi Zhuang Autonomous Region, China
  • Received:2022-09-24 Accepted:2022-11-08 Online:2023-12-08 Published:2023-04-22
  • Contact: Wang Bin, Chief physician, First Affiliated Hospital of Guangxi University of Chinese Medicine, Nanning 530023, Guangxi Zhuang Autonomous Region, China
  • About author:Xiong Bo, Master candidate, Graduate School of Guangxi University of Chinese Medicine, Nanning 530299, Guangxi Zhuang Autonomous Region, China
  • Supported by:
    School Level Project of Guangxi University of Chinese Medicine, No. YCXJ2021070 (to XB); Basic Research Ability Improvement Project of Young and Middle Aged Teachers of Guangxi Colleges and Universities, No. 2022KY0282 (to LJF); School Level Project of Guangxi University of Chinese Medicine, No. YCXJ2021071 (to HY)

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.

Key words: knee osteoarthritis, cuproptosis, prediction model, machine learning, immune infiltration, inflammatory factor, molecular subtype

CLC Number: