中国组织工程研究 ›› 2024, Vol. 28 ›› Issue (11): 1724-1729.doi: 10.12307/2024.224

• 组织构建相关数据分析 Date analysis of organization construction • 上一篇    下一篇

N6-甲基腺苷相关调节因子与骨关节炎:生物信息学和实验验证分析

袁长深1,廖书宁2,李  哲2,官岩兵2,吴思萍2,胡  琪2,梅其杰1,段  戡1   

  1. 1广西中医药大学第一附属医院四肢骨伤科,广西壮族自治区南宁市  530023;2广西中医药大学研究生院,广西壮族自治区南宁市  530000
  • 收稿日期:2023-02-14 接受日期:2023-03-22 出版日期:2024-04-18 发布日期:2023-07-27
  • 通讯作者: 段戡,博士,主任医师,广西中医药大学第一附属医院四肢骨伤科,广西壮族自治区南宁市 530023
  • 作者简介:袁长深,男,1978年生,广西壮族自治区荔浦市人,汉族,硕士,主要从事骨与关节疾病的基础与临床研究。
  • 基金资助:
    国家自然科学基金(82060875),项目负责人:袁长深;国家自然科学基金(82160912),项目负责人:段戡

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)

摘要:


文题释义:

骨关节炎:是一种以软骨退变、滑膜炎症和软骨下骨硬化为特征的退行性关节疾病,主要症状包括疼痛和活动障碍等,致残率高,目前全球至少有2.42亿人受到其困扰。
N6-甲基腺苷:是指RNA中腺苷的第6位氮原子处发生的甲基化修饰,占所有RNA甲基化修饰的80%以上,是真核生物中最丰富的mRNA修饰。N6-甲基腺苷作为一种可逆的动态表观遗传标记,参与RNA可变剪接、转运、翻译和降解等。


背景:越来越多证据表明N6-甲基腺苷(N6-methyladenosine,m6A)调节因子与骨关节炎密切相关,被认为是防治骨关节炎新方向,但具体作用机制不明。

目的:通过对骨关节炎基因芯片数据集进行生物信息学分析,探讨m6A对骨关节炎的作用,解析骨关节炎发病机制。
方法:首先利用R软件提取GEO数据库中GSE1919数据集中骨关节炎相关m6A调节因子及其表达量,进而对提取结果行基因差异分析及GO、KEGG富集分析;接着对PPI网络拓扑学分析结果和机器学习结果取交集得到m6A关键调节因子,并通过体外细胞实验验证。

结果与结论:①提取得到16个骨关节炎相关m6A调节因子表达量,通过差异分析获得ZC3H13、YTHDC1、YTHDF3、HNRNPC等11个m6A差异调节因子;②GO富集分析显示,骨关节炎相关m6A差异调节因子在生物过程中主要于mRNA转运、RNA分解代谢、胰岛素样生长因子受体信号通路调控等发挥作用;③KEGG富集分析显示,差异调节因子主要参与p53、白细胞介素17和AMPK信号通路;④综合PPI网络拓扑学分析和机器学习结果获得m6A关键调节因子——YTHDC1;⑤体外细胞实验结果表明,m6A关键调节因子——YTHDC1在对照组与骨关节炎组中表达存在显著差异(P < 0.05);⑥结果显示,YTHDC1与骨关节炎发生发展密切相关,有望成为m6A治疗骨关节炎的分子靶点。

https://orcid.org/0000-0001-5749-9859(袁长深)

中国组织工程研究杂志出版内容重点:组织构建;骨细胞;软骨细胞;细胞培养;成纤维细胞;血管内皮细胞;骨质疏松;组织工程

关键词: 骨关节炎, N6-甲基腺苷, 生物信息学, 机器学习, 调节因子, 软骨细胞, 实验验证

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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