DYRK2: a novel therapeutic target for rheumatoid arthritis combined with osteoporosis based on East Asian and European populations

doi:10.12307/2026.609

Abstract

Abstract: BACKGROUND: Studies have shown that rheumatoid arthritis and osteoporosis are positively correlated, but the causal relationship and related mechanisms have not yet been confirmed. With the cross-fertilization of computer science and life sciences, Mendelian randomization and bioinformatics analyses based on genome-wide association study (GWAS) and transcriptome sequencing data can assess the causal relationship between two diseases, explore the related mechanisms, and mine the therapeutic targets, which will be beneficial to the precision treatment of rheumatoid arthritis combined with osteoporosis.
OBJECTIVE: To explore the causal relationship between rheumatoid arthritis and osteoporosis using two-sample Mendelian randomization and to mine potential co-morbid targets and potential targeted drugs through summary-data-based Mendelian randomization and bioinformatics analyses, aiming to provide theoretical basis for mechanism exploration and precision treatment in the field of rheumatoid arthritis combined with osteoporosis.
METHODS: (1) Firstly, GWAS data of rheumatoid arthritis, osteoporosis, and cis-expression quantitative trait locus (cis-eQTL) in Asian and European populations were downloaded from the GWAS Catalog, IEU Open GWAS, FinnGen, and eQTLGen databases, and were used for two-sample Mendelian randomization analysis and summary-data-based Mendelian randomization analysis. (2) Transcriptome sequencing data of rheumatoid arthritis (GSE93272 and GSE15573) were downloaded from the GEO database for bioinformatics analysis. (3) Subsequently, forward and inverse Mendelian randomization analyses between rheumatoid arthritis and osteoporosis were performed, and inverse variance weighted was used as the main metric for the analyses, and the results were corroborated with MR Egger, simple mode, weighted median and weighted mode. (4) Then, the genes closely related to rheumatoid arthritis and osteoporosis were identified based on the summary-data-based Mendelian randomization analysis, and the co-disease targets of rheumatoid arthritis and osteoporosis were mined based on cross-analysis. Meanwhile, the biological functions of the co-morbid targets were verified based on bioinformatics analysis and cellular experiments. (5) In addition, a rheumatoid arthritis risk prediction nomogram was constructed based on DYRK2, and its prediction performance was verified by receiver operating characteristic curve, correction curve and decision curve. Finally, the target potential drugs were mined based on Enrichr database and molecular docking was performed.
RESULTS AND CONCLUSION: (1) Forward Mendelian randomization analysis of rheumatoid arthritis and osteoporosis showed statistically significant results except for GCST90044540 and GCST90086118, and all other results indicated a significant causal relationship and positive correlation between rheumatoid arthritis and osteoporosis. (2) Inverse Mendelian randomization analysis suggested that no significant causal relationship was seen between osteoporosis and rheumatoid arthritis. (3) Summary-data-based Mendelian randomization analysis identified a total of 412 and 344 genes positively associated with rheumatoid arthritis and osteoporosis, and 421 and 347 genes negatively associated. Based on the cross-analysis, 26 co-morbid genes were subsequently obtained. Among them, DYRK2 was a potential therapeutic target, and subsequent bioinformatics analysis and cellular experiments confirmed its important role in the progression of rheumatoid arthritis and osteoporosis. (4) Furthermore, the constructed nomogram has excellent predictive performance. Finally, four potential DYRK2-targeting drugs (undecanoic acid, metyrapone, JNJ-38877605, and ACA) were discovered and molecular docking also demonstrated reliable targeting ability. (5) In conclusion, based on GWAS data from Asian and European populations, we successfully demonstrated that rheumatoid arthritis and osteoporosis are causally related at the genetic level, DYRK2 is a potential therapeutic target, and four small molecules are potential target drugs.

Key words: rheumatoid arthritis, osteoporosis, Mendelian randomization, summary-data-based Mendelian randomization, co-disease genes, DYRK2

CLC Number:

Wu Zhilin, , He Qin, Wang Pingxi, Shi Xian, Yuan Song, Zhang Jun, Wang Hao . DYRK2: a novel therapeutic target for rheumatoid arthritis combined with osteoporosis based on East Asian and European populations[J]. Chinese Journal of Tissue Engineering Research, 2026, 30(6): 1569-1579.

Figures/Tables 11

态性，并通过去除连锁不平衡从IEU Open GWAS 数据库筛选出满足孟德尔随机化三大假设的单核苷酸多态性，随后剔除F < 10的单核苷酸多态性，以避免结果偏倚，最后进行类风湿关节炎和骨质疏松症间的正向双样本孟德尔随机化分析。结果显示，除外暴露GCST90044540和结局GCST90086118，其余孟德尔随机化分析证实类风湿关节炎和骨质疏松症之间存在因果关系，并且呈显著正相关(图2A)。此外，散点图显示，其余4种算法(MR Egger法、简单模式法、加权中位数法和加权模式法)具有一致性，表明分析结果可靠(图2B)。阳性结果均通过Cochran’s Q检验、MR-Egger-Intercept检验和留一法检验，证明结果稳定且可靠(图2C)。 2.2 骨质疏松症和类风湿关节炎的反向孟德尔随机化分析基于相同方式筛选出反向孟德尔随机化分析中与暴露因素(骨质疏松症)紧密相关且满足三大假设的单核苷酸多态性用于反向双样本孟德尔随机化分析。结果显示，尽管骨质疏松症与类风湿关节炎存在正相关趋势，但不存在明显因果关系(图3A)。散点图中各算法的不一致也证明骨质疏松症和类风湿关节炎之间不存在因果关系(图3B)。此外，敏感性分析结果表明骨质疏松症和类风湿关节炎的反向孟德尔随机化分析是可靠的(图3A和3C)。综上所述，类风湿关节炎和骨质疏松症的正向孟德尔随机化分析中具有一致方向的OR值，并且大部分结果具有显著性；同时，骨质疏松症和类风湿关节炎的反向孟德尔随机化分析中未见阳性结果。因此，类风湿关节炎与骨质疏松症之间具有因果关系，并且类风湿关节炎与骨质疏松症的发生风险呈显著正相关。 2.3 潜在治疗靶点挖掘基于SMR分析，该研究共获得与类风湿关节炎和骨质疏松症正相关的基因分别为412和344个，负相关基因分别为421和347个。对正相关基因和负相关基因进行两两交叉分析，最终得到6个共同正相关基因和20个共同负相关基因，见图4。这些基因在类风湿关节炎和骨质疏松症的调控中扮演桥梁作用，其中只有DYRK2的Beta值< -1.5，表明DYRK2与两种疾病具有紧密的联系(可能在两种疾病的共病机制中扮演着关键角色)，并且是潜在的治疗靶点(表3)。 2.4 DYRK2的生物学功能探索 GSE93272和GSE15573数据集中的基因差异表达分析表明，DYRK2在类风湿关节炎中显著低表达(图5A，B)，这表明DYRK2的表达可能是类风湿关节炎发病的机制之一。生物学功能分析表明DYRK2主要参与氨基酸的修饰(图5C)。此外，GSEA分析表明，DYRK2的表达对TNF信号通路、破骨细胞分化和PPAR通路具有抑制作用(图5D，E)。TNF信号通路是类风湿关节炎发病和进展的关键通路；破骨细胞分化和PPAR通路是骨质疏松发生的关键因素。因此，DYRK2低表达可能会导致这些通路的异常激活，进而导致类风湿关节炎的进展和骨质疏"

松症的发生。此外，GTEx数据库表明，DYRK2在骨髓中显著富集(图5F)，在成骨分化中可能发挥重要作用。因此，上述结果表明，DYRK2是类风湿关节炎和骨质疏松症的关键共病基因。 2.5 DYRK2的重要性评估和诺莫图构建单因素逻辑回归结果显示，DYRK2在GSE93272和GSE15573两个数据集中具有显著意义(图6A)；受试者工作特征曲线和混淆矩阵均显示DYRK2基因在两个数据集中表现出色。因此，DYRK2基因具有较好的类风湿关节炎风险预测性能(图6B，C)。此外，相关性分析表明，除年龄外，DYRK2的表达量与临床疾病活动指数(clinical disease activity index，CDAI)简化临床疾病活动指数(simplified disease activity index，SDAI )和目测类比评分(visual analogue scale，VAS)均呈显著负相关(图6D)，这证实了该基因在临床中的重要性。最后，基于DYRK2和年龄特征，构建了一个诺莫图用于预测类风湿关节炎患病风险(图6E)。受试者工作特征曲线、矫正曲线和决策曲线证明该预测工具具有出色的预测性能(图6F-H)。 2.6 基于细胞实验验证DYRK2的生物学功能如图7A所示，si-DYRK2转染成功，DYRK2表达明显下调。如图7B，C所示，在MC3T3-E1细胞中沉默DYRK2表达时，成骨相关基因(碱性磷酸酶、骨桥蛋白、骨钙素、Runt 相关转录因子2) mRNA和蛋白表达显著降低；同时，通过碱性磷酸酶染色和茜素红染色发现当DYRK2表达降低时，它能够显著抑制MC3T3-E1细胞的成骨分化和矿化(图7D-G)，这表明DYRK2基因在成骨过程中起调控作用。 2.7 DYRK2的靶向药物挖掘和分子对接基于Enrichr数据库挖掘出4种可靶向DYRK2的药物(图8A)。分子对接显示，4种药物的小分子均成功占据在DYRK2蛋白的分子口袋中(图8B)，结合能分别为-23.85 kJ/mol (Undecanoic Acid)、-30.96 kJ/mol (Metyrapone)、-46.86 kJ/mol(JNJ-38877605)和-38.07 kJ/mol (ACA)。这些结果为类风湿关节炎和骨质疏松症的靶向治疗提供了一定的前期理论依据。"

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