Shi Xiangwen, Ni Haonan, Wu Yipeng, Guo Minzheng, Wang Bin, Zhang Yue, Zhang Bihuan, Xu Yongqing
School of Medicine, Kunming Medical University, Kunming, China.
Department of Orthopedic Surgery, 920th Hospital of Joint Logistics Support Force, Kunming, China.
Front Genet. 2022 Dec 5;13:1044264. doi: 10.3389/fgene.2022.1044264. eCollection 2022.
As a recurrent inflammatory bone disease, the treatment of osteomyelitis is always a tricky problem in orthopaedics. N6-methyladenosine (m6A) regulators play significant roles in immune and inflammatory responses. Nevertheless, the function of m6A modification in osteomyelitis remains unclear. Based on the key m6A regulators selected by the GSE16129 dataset, a nomogram model was established to predict the incidence of osteomyelitis by using the random forest (RF) method. Through unsupervised clustering, osteomyelitis patients were divided into two m6A subtypes, and the immune infiltration of these subtypes was further evaluated. Validating the accuracy of the diagnostic model for osteomyelitis and the consistency of clustering based on the GSE30119 dataset. 3 writers of Methyltransferase-like 3 (METTL3), RNA-binding motif protein 15B (RBM15B) and Casitas B-lineage proto-oncogene like 1 (CBLL1) and three readers of YT521-B homology domain-containing protein 1 (YTHDC1), YT521-B homology domain-containing family 3 (YTHDF2) and Leucine-rich PPR motif-containing protein (LRPPRC) were identified by difference analysis, and their Mean Decrease Gini (MDG) scores were all greater than 10. Based on these 6 significant m6A regulators, a nomogram model was developed to predict the incidence of osteomyelitis, and the fitting curve indicated a high degree of fit in both the test and validation groups. Two m6A subtypes (cluster A and cluster B) were identified by the unsupervised clustering method, and there were significant differences in m6A scores and the abundance of immune infiltration between the two m6A subtypes. Among them, two m6A regulators (METTL3 and LRPPRC) were closely related to immune infiltration in patients with osteomyelitis. m6A regulators play key roles in the molecular subtypes and immune response of osteomyelitis, which may provide assistance for personalized immunotherapy in patients with osteomyelitis.
作为一种复发性炎性骨病，骨髓炎的治疗一直是骨科领域棘手的问题。N6-甲基腺苷（m6A）调节剂在免疫和炎症反应中发挥重要作用。然而，m6A修饰在骨髓炎中的功能仍不清楚。基于GSE16129数据集筛选出的关键m6A调节剂，采用随机森林（RF）方法建立了列线图模型来预测骨髓炎的发病率。通过无监督聚类，将骨髓炎患者分为两种m6A亚型，并进一步评估这些亚型的免疫浸润情况。基于GSE30119数据集验证骨髓炎诊断模型的准确性和聚类的一致性。通过差异分析确定了甲基转移酶样3（METTL3）、RNA结合基序蛋白15B（RBM15B）和类Casitas B系原癌基因1（CBLL1）这3个写者以及含YT521-B同源结构域蛋白1（YTHDC1）、含YT521-B同源结构域家族3（YTHDF2）和富含亮氨酸的PPR基序蛋白（LRPPRC）这3个读者，它们的平均减少基尼系数（MDG）得分均大于10。基于这6个重要的m6A调节剂，开发了列线图模型来预测骨髓炎的发病率，拟合曲线表明在测试组和验证组中拟合度都很高。通过无监督聚类方法确定了两种m6A亚型（A簇和B簇），两种m6A亚型在m6A得分和免疫浸润丰度方面存在显著差异。其中，两个m6A调节剂（METTL3和LRPPRC）与骨髓炎患者的免疫浸润密切相关。m6A调节剂在骨髓炎的分子亚型和免疫反应中起关键作用，这可能为骨髓炎患者的个性化免疫治疗提供帮助。
