中国组织工程研究

中国组织工程研究 ›› 2026, Vol. 30 ›› Issue (29): 7749-7754.doi: 10.12307/2026.277

• 组织工程相关大数据分析 Big data analysis in tissue engineering • 上一篇    下一篇

确定脊柱骨关节炎潜在药物靶点的孟德尔随机化分析

赵瑞凯1，王  玉1，郭晓辉1，孙泽华2，王  旭1   

  1. 1唐山市第二医院骨科，河北省唐山市   063000；2唐山市丰南区中医院康复科，河北省唐山市   063000
  • 收稿日期:2025-08-14 修回日期:2025-12-15 出版日期:2026-10-18 发布日期:2026-03-09
  • 通讯作者: 王旭，主任医师，唐山市第二医院骨科，河北省唐山市 063000
  • 作者简介:赵瑞凯，男，1990年生，河北省邢台市人，汉族，2018年河北医科大学毕业，硕士，工作于唐山市第二医院，主要从事骨科方面的研究。

Mendelian randomization analysis identifies potential drug targets for spinal osteoarthritis

Zhao Ruikai1, Wang Yu1, Guo Xiaohui1, Sun Zehua2, Wang Xu1   

  1. 1Department of Orthopedics, Tangshan Second Hospital, Tangshan 063000, Hebei Province, China; 2Department of Rehabilitation, Fengnan District Hospital of Traditional Chinese Medicine, Tangshan 063000, Hebei Province, China
  • Received:2025-08-14 Revised:2025-12-15 Online:2026-10-18 Published:2026-03-09
  • Contact: Wang Xu, Chief physician, Department of Orthopedics, Tangshan Second Hospital, Tangshan 063000, Hebei Province, China
  • About author:Zhao Ruikai, MS, Department of Orthopedics, Tangshan Second Hospital, Tangshan 063000, Hebei Province, China

PDF

16

摘要：



文题释义：
孟德尔随机化：是一种基于遗传变异的因果推断方法，通过将与暴露因素相关的遗传变异(如单核苷酸多态性)作为工具变量，模拟随机对照试验的设计，以评估暴露因素与疾病结局之间的因果关系。该方法能够有效减少混杂因素和反向因果的问题，常用于流行病学研究中探索潜在的病因关系。
分子对接：是一种计算模拟技术，用于预测2个分子之间的相互作用方式，尤其是小分子药物与靶点蛋白的结合情况。通过计算结合构象和亲和力，分子对接可以辅助识别潜在的药物分子、分析其作用机制，是药物设计和结构生物学研究中的重要工具。

背景：脊柱骨关节炎作为常见的退行性脊柱疾病，严重影响患者的生活质量，但其确切的分子机制尚未明确。
目的：通过孟德尔随机化分析方法识别与脊柱骨关节炎有因果关系的血浆蛋白，为该疾病领域寻找新的潜在治疗靶点提供借鉴。
方法：蛋白质数据从deCODE Genetics公司的数据库获取(共纳入35 559例冰岛个体，检测了4 907种血浆蛋白的遗传关联信息，https://www.decode.com/summarydata/)，脊柱骨关节炎的数据从骨关节炎遗传学联盟获取(共有826 690个样本，可通过https://msk.hugeamp.org/downloads.html免费下载)，所有数据均为开源并符合伦理要求。使用Wald比值法或逆方差加权法评估4 907个血浆蛋白与脊柱骨关节炎之间的因果关系，对P值进行Bonferroni校正。此外进行Steiger方向性检验排除反向因果、共定位分析排除连锁不平衡、表型扫描排除水平多效性、外部验证排除偶然发现。最终借助在线分析工具Enrichr对靶向因果蛋白的小分子化合物进行筛选，并针对排名最前的化合物实施分子对接，旨在预测它们与蛋白质的结合模式及能量，从而明确最稳定且可能的结合方式。
结果与结论：①4 907中蛋白中筛选出了1 553个蛋白的1 878个显著蛋白质数量性状位点，孟德尔随机化分析后有4种蛋白被鉴定出与脊柱骨关节炎存在较强的因果关系，分别为单核CD14、白细胞介素12β亚基(IL12B)、肝细胞生长因子样蛋白(MST1)以及Semaphorin-4A (SEMA4A)，其中IL12B与脊柱骨关节炎呈负相关，其余则与脊柱骨关节炎呈正相关；②同时药物预测结果显示，靶向CD14的特斯米利芬、靶向IL12B的孟鲁司特、靶向MST1的萘胺和靶向SEMA4A的水仙碱在分子对接中均表现出良好的结合能力，最低结合能均低于-6.0 kJ/mol；③综合分析表明，这4种血浆蛋白质或可作为临床脊柱骨关节炎筛查、预防及干预的潜在生物标志物或药物研发靶点，亦可为国内人群开展相关研究提供理论依据和参考价值。

https://orcid.org/0009-0006-5712-7880 (赵瑞凯) 


中国组织工程研究杂志出版内容重点：干细胞；骨髓干细胞；造血干细胞；脂肪干细胞；肿瘤干细胞；胚胎干细胞；脐带脐血干细胞；干细胞诱导；干细胞分化；组织工程

关键词: 血浆蛋白, 脊柱骨关节炎, 孟德尔随机化, 贝叶斯共定位, 表型扫描, 分子对接

Abstract: BACKGROUND: Spinal osteoarthritis is a common degenerative spinal disease that severely affects quality of life of patients, but its exact molecular mechanism remains unclear. 
OBJECTIVE: To identify plasma proteins related to spinal osteoarthritis through Mendelian randomization analysis and provide a reference for finding new potential therapeutic targets in this disease field.
METHODS: Protein data were obtained from the deCODE Genetics database (A total of 35 559 Icelandic individuals were included, and genetic association information of 4 907 plasma proteins was detected, https://www.decode.com/summarydata/). Spinal osteoarthritis data were obtained from the Osteoarthritis Genetics Consortium (A total of 826 690 samples are available for free download via https://msk.hugeamp.org/downloads.html). All data are open source and comply with ethical requirements. Wald ratio or inverse variance weighting was used to assess the causal relationship between 4 907 plasma proteins and spinal osteoarthritis, with Bonferroni correction applied to the P-values. In addition, Steiger directional test was performed to exclude reverse causality; colocalization analysis was performed to exclude linkage disequilibrium; phenotype scanning was performed to exclude horizontal pleiotropy, and external validation was performed to exclude accidental findings. Finally, the online analysis tool Enrichr was used to screen small-molecule compounds targeting causal proteins. Molecular docking was performed on the top-ranked compounds to predict their binding patterns and energies with proteins, thus identifying the most stable and potential binding modes.
RESULTS AND CONCLUSION: (1) Among 4 907 proteins, 1 878 significant protein quantitative trait locus were screened from 1 553 proteins. After Mendelian randomization analysis, four proteins were identified to have a strong causal relationship with spinal osteoarthritis, namely monocytic CD14, interleukin-12 beta subunit, hepatocyte growth factor-like protein, and Semaphorin-4A. Among them, interleukin-12 beta subunit was negatively correlated with spinal osteoarthritis, while the remaining proteins were positively correlated with spinal osteoarthritis. (2) Additionally, drug prediction results showed that tesmilifene targeting CD14, montelukast targeting interleukin-12 beta subunit, naphthalenamine targeting hepatocyte growth factor-like protein, and lycorine targeting semaphorin-4A all demonstrated good binding affinity in molecular docking, with minimum binding energies below -6.0 kJ/mol. (3) Comprehensive analysis suggest that these four plasma proteins may serve as potential biomarkers or drug development targets for clinical screening, prevention, and intervention of spinal osteoarthritis, and also provide theoretical basis and reference value for related studies in the Chinese population.

Key words: plasma proteins, spinal osteoarthritis, Mendelian randomization, Bayesian colocalization, phenotype scanning, molecular docking

中图分类号: