Chinese Journal of Tissue Engineering Research ›› 2024, Vol. 28 ›› Issue (11): 1724-1729.doi: 10.12307/2024.224

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N6-methyladenosine related regulatory factors in osteoarthritis: bioinformatics analysis and experimental validation

Yuan Changshen1, Liao Shuning2, Li Zhe2, Guan Yanbing2, Wu Siping2, Hu Qi2, Mei Qijie1, Duan Kan1   

  1. 1Orthopedic Department of the Limbs, The First Affiliated Hospital of Guangxi University of Chinese Medicine, Nanning 530023, Guangxi Zhuang Autonomous Region, China; 2Guangxi University of Chinese Medicine, Nanning 530000, Guangxi Zhuang Autonomous Region, China
  • Received:2023-02-14 Accepted:2023-03-22 Online:2024-04-18 Published:2023-07-27
  • Contact: Duan Kan, MD, Chief physician, Orthopedic Department of the Limbs, The First Affiliated Hospital of Guangxi University of Chinese Medicine, Nanning 530023, Guangxi Zhuang Autonomous Region, China
  • About author:Yuan Changshen, Master, Orthopedic Department of the Limbs, The First Affiliated Hospital of Guangxi University of Chinese Medicine, Nanning 530023, Guangxi Zhuang Autonomous Region, China
  • Supported by:
    National Natural Science Foundation of China, Nos. 82060875 (to YCS) and 82160912 (to DK)

Abstract: BACKGROUND: Increasing evidence suggests that N6-methyladenosine (m6A) regulators are closely associated with osteoarthritis and are considered to be a new direction in the prevention and treatment of osteoarthritis, but their specific mechanism of action is unknown. 
OBJECTIVE: To conduct a bioinformatics analysis of the osteoarthritis gene microarray dataset in order to explore the role of m6A in osteoarthritis and analyze the pathogenesis of osteoarthritis. 
METHODS: The m6A regulators associated with osteoarthritis and their expression were first extracted from the GSE1919 dataset in the GEO database using R software, and then the results were analyzed by gene difference analysis and GO and KEGG enrichment analyses. Subsequently, the results of protein-protein interaction network topology analysis and machine learning results were intersected to obtain the m6A Hub regulators, which were validated by in vitro cellular experiments. 
RESULTS AND CONCLUSION: A total of 16 osteoarthritis-related m6A regulators were extracted and 11 m6A differential regulators, including ZC3H13, YTHDC1, YTHDF3 and HNRNPC, were obtained by differential analysis. GO enrichment analysis showed that osteoarthritis-related m6A differential regulators played a role in the biological processes such as mRNA transport, RNA catabolism, and regulation of insulin-like growth factor receptor signaling pathway. (3) KEGG enrichment analysis showed that the differential regulators were mainly involved in the p53, interleukin-17 and AMPK signaling pathways. The combined protein-protein interaction network topology analysis and machine learning results obtained the m6A Hub regulator - YTHDC1. (5) The results of in vitro cellular experiments showed that there was a significant difference in the expression of m6A key regulator between the control and experimental groups (P < 0.05). To conclude, YTHDC1 is closely related to the development of osteoarthritis, which is expected to be a molecular target of m6A for the treatment of osteoarthritis.

Key words: osteoarthritis, N6-methyladenosine, bioinformatics, machine learning, regulator factor, chondrocyte, experimental verification

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