The 6th Affiliated Hospital of Kunming Medical University, Yuxi, Yunnan, China.
Dali University, Dali, Yunnan, China.
Biochem Genet. 2024 Oct;62(5):3467-3484. doi: 10.1007/s10528-023-10610-7. Epub 2023 Dec 19.
m6A modification is the most abundant mRNA modifications and plays an integral role in various biological processes in eukaryotes. However, the role of m6A regulators in rheumatoid arthritis remains unknown. To determine the expression of m6A RNA methylation regulators in rheumatoid arthritis and their possible functional and prognostic value. In this study, we performed differential analysis in the comprehensive gene expression database GSE93272 dataset between non-rheumatoid arthritis patients and rheumatoid arthritis patients to obtain 15 important m6A regulators. A random forest model and lasso regression were used to screen the five most important m6A regulators to predict the risk of developing rheumatoid arthritis. After further validation using in vitro qPCR experiments, a nomogram model was developed based on the four most important m6A regulators (ELAVL1, WTAP, YTHDF1, and ALKBH5). Immuno-infiltration analysis and consensus clustering analysis were then performed. An analysis of the decision curve showed that the nomogram model could be beneficial to patients. According to selected important m6A regulators, patients with rheumatoid arthritis were classified into two m6A models (ClusterA and ClusterB) via consensus approach. Activated B cells, CD56dim natural killer cells, immature B cells, monocytes, natural killer T cells, and T lymphocytes were associated with ClusterA in immune infiltration analysis. Importantly, immune infiltration in patients with high ELAVL1 expression was strikingly similar to ClusterA. m6A regulators play a non-negligible role in the development of rheumatoid arthritis. A study of m6A patterns may provide future therapeutic options for rheumatoid arthritis.
m6A 修饰是最丰富的 mRNA 修饰之一，在真核生物的各种生物过程中发挥着重要作用。然而，m6A 调节剂在类风湿关节炎中的作用尚不清楚。为了确定 m6A RNA 甲基化调节剂在类风湿关节炎中的表达及其可能的功能和预后价值。在这项研究中，我们在综合基因表达数据库 GSE93272 中对非类风湿关节炎患者和类风湿关节炎患者之间进行了差异分析，以获得 15 个重要的 m6A 调节剂。随机森林模型和套索回归用于筛选五个最重要的 m6A 调节剂，以预测发生类风湿关节炎的风险。进一步通过体外 qPCR 实验验证后，基于四个最重要的 m6A 调节剂（ELAVL1、WTAP、YTHDF1 和 ALKBH5）建立了列线图模型。然后进行免疫浸润分析和共识聚类分析。决策曲线分析表明，列线图模型对患者有益。根据选定的重要 m6A 调节剂，通过共识方法将类风湿关节炎患者分为两个 m6A 模型（ClusterA 和 ClusterB）。免疫浸润分析中，激活的 B 细胞、CD56dim 自然杀伤细胞、未成熟 B 细胞、单核细胞、自然杀伤 T 细胞和 T 淋巴细胞与 ClusterA 相关。重要的是，高表达 ELAVL1 患者的免疫浸润与 ClusterA 非常相似。m6A 调节剂在类风湿关节炎的发展中起着不可忽视的作用。对 m6A 模式的研究可能为类风湿关节炎提供未来的治疗选择。
