中国组织工程研究

中国组织工程研究 ›› 2026, Vol. 30 ›› Issue (10): 2629-2640.doi: 10.12307/2026.617

• 组织构建相关数据分析 Date analysis of organization construction • 上一篇    下一篇

炎症因子与类风湿关节炎的关系：芬兰R10数据库及全基因组关联大样本分析

姜  凯1，戎义发1，贾海峰1，李翰政1，卢博文1，梁学振1，李  刚2   

  1. 1山东中医药大学第一临床医学院，山东省济南市  250355；2山东中医药大学附属医院显微骨科，山东省济南市  250014


  • 收稿日期:2025-03-01 接受日期:2025-06-13 出版日期:2026-04-08 发布日期:2025-09-01
  • 通讯作者: 李刚，博士，博士生导师，山东中医药大学附属医院显微骨科，山东省济南市 250014
  • 作者简介:姜凯，男，2000年生，山东省烟台市人，汉族，山东中医药大学在读硕士，主要从事中医骨伤科学方面的研究。

Relationship between inflammatory factors and rheumatoid arthritis: a large-sample analysis based on the FinnGen R10 database and genome-wide association studies

Jiang Kai1, Rong Yifa1, Jia Haifeng1, Li Hanzheng1, Lu Bowen1, Liang Xuezhen1, Li Gang2   

  1. 1The First Clinical Medical College of Shandong University of Traditional Chinese Medicine, Jinan 250355, Shandong Province, China; 2Department of Micro-Orthopedics, The Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan 250014, Shandong Province, China
  • Received:2025-03-01 Accepted:2025-06-13 Online:2026-04-08 Published:2025-09-01
  • Contact: Li Gang, MD, Doctoral supervisor, Department of Micro-Orthopedics, The Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan 250014, Shandong Province, China
  • About author:Jiang Kai, MS candidate, The First Clinical Medical College of Shandong University of Traditional Chinese Medicine, Jinan 250355, Shandong Province, China

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摘要：


文题释义：
孟德尔随机化：是一种基于遗传学的分析方法，利用遗传变异作为工具变量，可以评估暴露因素与疾病结果之间的因果关系。核心在于利用遗传变异的随机分配特性，避免传统观察性研究中的混杂偏倚和反向因果问题，从而为炎症因子与类风湿关节炎之间的因果关系提供了更可靠的证据。
类风湿关节炎：是一种慢性、系统性的自身免疫性疾病，主要表现为关节炎症、滑膜炎和骨质破坏。类风湿关节炎的发病机制复杂，涉及多种炎症因子和代谢物的相互作用。

背景：类风湿关节炎是一种慢性、系统性的自身免疫性疾病，它的发病机制涉及多种炎症因子和代谢物，但因果关系尚不明确。国内类风湿关节炎的诊断和治疗水平近年来虽有提高，但仍有部分患者因缺乏早期诊断和规范治疗而致残。
目的：采用孟德尔随机化方法评估炎症因子与类风湿关节炎之间的潜在因果关系，为临床研究提供新的支持和角度，以期填补类风湿关节炎发病机制与炎症因子关系的空缺，为治疗和预防类风湿关节炎提供新的潜在靶点和指导。
方法：疾病数据使用了来自一项芬兰R10数据库的13 621例类风湿关节炎患者和262 844例健康对照者的遗传数据；91种炎症因子来自全基因组关联研究11个队列的荟萃分析，共有14 824名欧洲血统参与者。正向孟德尔随机化分析以P < 5×10-6来识别炎症因子和类风湿关节炎相关的工具变量；反向孟德尔随机化分析以P < 5×10-8来识别类风湿关节炎和炎症因子相关的工具变量；正向和反向连锁不平衡参数均设为0.001，遗传距离设为 10 000 kb，只考虑F统计量> 10的工具变量，之后去除混杂因素。采用逆方差加权方法、MR-Egger、加权中位数、简单众数和加权众数等方法研究91个炎症因子与类风湿关节炎之间的因果关系，主要以逆方差加权方法为主，P < 0.05；异质性和水平多效性P > 0.05，以排除异质性和水平多效性；并且进行反向孟德尔随机化分析，以排除反向因果。
结果与结论：①C-C趋化因子23(OR=0.921，P=0.006)、成纤维细胞生长因子19(OR=0.906，P=0.046)、白细胞介素12亚单位β(OR=0.899，P=0.009)、白细胞介素2(OR=0.889，P=0.024)、白血病抑制因子受体(OR=0.876，P=0.047)对类风湿关节炎起保护作用；②C-C趋化因子19(OR=1.118，P=0.032)、C-C趋化因子4(OR=1.107，P=0.004)、白细胞介素7(OR=1.211，P=0.018)、肿瘤坏死因子(OR=1.119，P=0.040)对类风湿关节炎起危险作用；③上述结果为炎症因子在类风湿关节炎中的作用提供了新的视角和证据，弥补了该领域的空缺，并可能为预防和治疗类风湿关节炎带来新策略。
https://orcid.org/0009-0002-4327-6130(姜凯)

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: 孟德尔随机化, 炎症因子, 类风湿关节炎, 因果关系, 全基因组关联研究, 单核苷酸多态性, 保护性因子, 危险性因子

Abstract: BACKGROUND: Rheumatoid arthritis is a chronic, systemic autoimmune disease, and its pathogenesis involves multiple inflammatory factors and metabolites. However, the causal relationships are not yet clear. In China, although the diagnosis and treatment of rheumatoid arthritis have improved in recent years, some patients still suffer from disabilities due to a lack of early diagnosis and standardized treatment.
OBJECTIVE: To assess the potential causal relationships between inflammatory factors and rheumatoid arthritis using Mendelian randomization methods, providing new support and perspectives for clinical research in order to fill the gap in the understanding of the relationship between the pathogenesis of rheumatoid arthritis and inflammatory factors, thereby providing new potential targets and guidance for the treatment and prevention of rheumatoid arthritis.
METHODS: The disease data were obtained from a genome-wide association study in the FinnGen R10 database, including genetic data from 13 621 patients with rheumatoid arthritis and 262 844 healthy controls. The 91 inflammatory factors were derived from a meta-analysis of 11 cohorts, involving 14 824 participants of European descent. For the forward Mendelian randomization analysis, a P-value of < 5 × 10−6 was used to identify instrumental variables related to inflammatory factors and rheumatoid arthritis. For the reverse Mendelian randomization analysis, a P-value of < 5 × 10−8 was used to identify instrumental variables related to rheumatoid arthritis and inflammatory factors. The linkage disequilibrium parameters for both forward and reverse analyses were set at 0.001, and the genetic distance was set at 10 000 kb. Only instrumental variables with an F-statistic greater than 10 were considered, and confounding factors were removed. The causal relationships between the 91 inflammatory factors and rheumatoid arthritis were studied using methods such as inverse variance weighting, MR-Egger, weighted median, simple mode, and weighted mode, with inverse variance weighting being the primary method. A P-value of < 0.05 was considered significant. Heterogeneity and horizontal pleiotropy were excluded if their P-values were > 0.05. Reverse Mendelian randomization analysis was also conducted to exclude reverse causality.
RESULTS AND CONCLUSION: (1) C-C motif chemokine 23 [odds ratio (OR): 0.921, P=0.006], fibroblast growth factor 19 (OR=0.906, P=0.046), interleukin-12 subunit beta (OR=0.899, P=0.009), interleukin-2 (OR=0.889, P=0.024), and leukemia inhibitory factor receptor (OR=0.876, P=0.047) have protective effects on rheumatoid arthritis. (2) In contrast, C-C motif chemokine 19 (OR=1.118, P=0.032), C-C motif chemokine 4 (OR=1.107, P=0.004), interleukin-7 (OR=1.211, P=0.018), and tumor necrosis factor (OR=1.119, P=0.040) have detrimental effects on rheumatoid arthritis. These findings provide new insights and evidence for the role of inflammatory factors in rheumatoid arthritis, filling the gap in this field and potentially leading to new strategies for the prevention and treatment of rheumatoid arthritis.

Key words: Mendelian randomization, inflammatory factors, rheumatoid arthritis, causal relationship, genome-wide association study, single nucleotide polymorphism, protective factors, risk factors

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