Lu Chengyang, Xu Yanan, Chen Shuai, Guo Li, Li Pengcui, Wei Xiaochun, Rong Xueqin
Department of Orthopedics, Shanxi Key Laboratory of Bone and Soft Tissue Injury Repair, Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
Department of Laboratory, Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
PLoS One. 2025 Feb 11;20(2):e0316824. doi: 10.1371/journal.pone.0316824. eCollection 2025.
Osteoarthritis (OA) is a prevalent chronic joint disease for which there is a lack of effective treatments. In this study, we used Mendelian randomization analysis to identify circulating proteins that are causally associated with OA-related traits, providing important insights into potential drug targets for OA.
Causal associations between 1553 circulating proteins and five OA-related traits were assessed in large-scale two-sample MR analyses using Wald ratio or inverse variance weighting, and the results were corrected for Bonferroni. In addition, sensitivity analyses were performed to validate the reliability of the MR results, including reverse MR analysis and Steiger filtering to ensure the causal direction between circulating proteins and OA; Bayesian co-localization and phenotypic scanning were used to eliminate confounding effects and horizontal pleiotropy. External validation was performed to exclude incidental findings using novel plasma protein quantitative trait loci. Finally, the online analysis tool Enrichr was utilized to screen drugs and molecular docking was performed to predict binding modes and energies between proteins and drugs to identify the most stable and likely binding modes and drugs.
Four proteins were ultimately found to be reliably and causally associated with three OA-related features: DNAJB12 and USP8 were associated with knee OA, IL12B with spinal OA, and RGMB with thumb OA. The ORs for the above proteins were 1.51 (95% CI, 1.26-1.81), 1.72 (95% CI, 1.42-2.08), 0.87 (95% CI, 0.81-0.92), and 0.59 (95% CI, 0.47-0.75), respectively. Drug-predicting small molecules (doxazosin, XEN 103, and montelukast) that simultaneously target three proteins, DNAJB12, USP8, and IL12B, docked well.
Based on our comprehensive analysis, we can draw the conclusion that there is a causal relationship between the genetic levels of DNAJB12, USP8, IL12B, and RGMB and the risk of respective OA.They may be potential options for OA screening and prevention in clinical practice. They can also serve as candidate molecules for future mechanism exploration and drug target selection.
骨关节炎(OA)是一种常见的慢性关节疾病,目前缺乏有效的治疗方法。在本研究中,我们使用孟德尔随机化分析来确定与OA相关性状有因果关系的循环蛋白,为OA的潜在药物靶点提供重要见解。
在大规模两样本MR分析中,使用Wald比率或逆方差加权评估1553种循环蛋白与五种OA相关性状之间的因果关系,并对结果进行Bonferroni校正。此外,进行敏感性分析以验证MR结果的可靠性,包括反向MR分析和Steiger过滤,以确保循环蛋白与OA之间的因果方向;使用贝叶斯共定位和表型扫描来消除混杂效应和水平多效性。利用新的血浆蛋白数量性状位点进行外部验证以排除偶然发现。最后,使用在线分析工具Enrichr筛选药物,并进行分子对接以预测蛋白质与药物之间的结合模式和能量,以确定最稳定和可能的结合模式及药物。
最终发现四种蛋白与三种OA相关特征有可靠的因果关系:DNAJB12和USP8与膝关节OA相关,IL12B与脊柱OA相关,RGMB与拇指OA相关。上述蛋白的比值比分别为1.51(95%可信区间,1.26 - 1.81)、1.72(95%可信区间,1.42 - 2.08)、0.87(95%可信区间,0.81 - 0.92)和0.59(95%可信区间,0.47 - 0.75)。同时靶向三种蛋白DNAJB12、USP8和IL12B的药物预测小分子(多沙唑嗪、XEN 103和孟鲁司特)对接良好。
基于我们的综合分析,可以得出结论,DNAJB12、USP8、IL12B和RGMB的基因水平与各自OA的风险之间存在因果关系。它们可能是临床实践中OA筛查和预防的潜在选择。它们还可作为未来机制探索和药物靶点选择的候选分子。