摘要
背景:研究已证明循环炎症蛋白和免疫细胞与类风湿关节炎之间的关联性,但因果关系尚不明确。目的:探究免疫细胞介导下循环炎症蛋白与类风湿关节炎的因果关系。方法:从GWAS Catalog数据库(由美国国家人类基因组研究所与欧洲生物信息学研究所联合创建并维护,为开放数据库)下载循环炎症蛋白和免疫细胞表型数据,从FinnGen数据库(是芬兰国内研究机构和生物样本库与国际行业伙伴合作的基因组学项目,为开放数据库)下载类风湿关节炎全基因组关联研究数据,进行两步孟德尔随机化分析:使用逆方差加权法评估91种循环炎症蛋白和731种免疫细胞对类风湿关节炎风险的因果影响,并辅助以MR-Egger、加权中位数、加权模式、简单模式和敏感性分析;评估已识别免疫细胞对循环炎症蛋白与类风湿关节炎之间关系的介导作用。结果与结论:①逆方差加权法分析结果表明,4种循环炎症蛋白与类风湿关节炎风险存在显著相关性,其中1种循环炎症蛋白是类风湿关节炎的危险因素,3种循环炎症蛋白是类风湿关节炎的保护因素;46种免疫细胞与类风湿关节炎存在显著相关性,其中20种免疫细胞是类风湿关节炎的危险因素,26种免疫细胞是是类风湿关节炎的保护因素。反向孟德尔随机化分析未发现类风湿关节炎与已识别的4种循环炎症蛋白存在因果关联。敏感性分析未发现显著的异质性和水平多效性。进一步中介分析结果显示,CD19 on IgD-CD38br在一定程度上介导了白细胞介素18(β=0.064,OR=1.066,P=0.044)与类风湿关节炎的因果效应,中介效应为0.004,中介占比为5.7%,直接效应为0.060。②研究结果揭示了循环炎症蛋白和免疫细胞与类风湿关节炎之间的因果关联,发现CD19 on IgD-CD38br在白细胞介素18与类风湿关节炎的因果关联中起部分介导作用。针对中国生物医学科研领域,可参考国际多组学研究平台与跨种族队列数据的整合分析框架,构建中国人群专属的表观基因组、蛋白质组及代谢组联合数据库,揭示复杂疾病发生发展的分子调控网络,助力疾病分型与早期诊断标志物开发;通过学习跨国协作研究机制,建立中国多民族、多地域的自然人群队列,系统解析环境暴露与基因交互作用对健康的影响,为制定本土化疾病预防策略提供科学依据。
BACKGROUND:Studies have shown that circulating inflammatory proteins and immune cells are associated with rheumatoid arthritis,but the causal relationship is unclear.OBJECTIVE:To explore the causal relationships between circulating inflammatory proteins and rheumatoid arthritis mediated by immune cells.METHODS:We downloaded data on circulating inflammatory proteins and immune cell phenotypes from the GWAS Catalog database(a publicly accessible database jointly established and maintained by the National Human Genome Research Institute and the European Bioinformatics Institute),and genome-wide association study data for rheumatoid arthritis from the FinnGen database(a genomics project resulting from collaboration between Finnish research institutions,biobanks,and international industry partners,also publicly accessible).A two-step Mendelian randomization analysis was then conducted.In the first step,inverse variance weighted method was used to evaluate the causal effects of 91 circulating inflammatory proteins and 731 immune cells on rheumatoid arthritis risk.MR-Egger,weighted median,weighted mode,simple mode,and sensitivity analyses were performed to ensure robustness and assess pleiotropy.The second step evaluated the mediating effects of identified immune cells on the relationship between circulating inflammatory proteins and rheumatoid arthritis.RESULTS AND CONCLUSION:(1)Inverse variance weighted analysis showed that four circulating inflammatory proteins were significantly correlated with the risk of rheumatoid arthritis,with one circulating inflammatory protein being a risk factor for rheumatoid arthritis and three circulating inflammatory proteins being protective factors for rheumatoid arthritis.Forty-six kinds of immune cells were significantly associated with rheumatoid arthritis,comprising 20 risk factors and 26 protective factors.Reverse Mendelian randomization analysis found no causal associations between rheumatoid arthritis and four identified circulating inflammatory proteins.Sensitivity analyses revealed no significant heterogeneity or horizontal pleiotropy.Further Mediation analysis showed that CD19 on IgD-CD38br partially mediated the causal effect of interleukin-18 on rheumatoid arthritis(β=0.064,odds ratio=1.066,P=0.044),with a mediation effect of 0.004,accounting for 5.7%of the total effect,and a direct effect of 0.060.(2)The study findings reveal that circulating inflammatory proteins and immune cells have causal associations with rheumatoid arthritis,and demonstrate that CD19 on IgD-CD38br partially mediates the causal effect of interleukin-18 on rheumatoid arthritis.With the rich accumulation of data in international multi-omics research platforms and trans-ethnic cohorts,China can reference their multi-dimensional data integration frameworks to construct a dedicated database integrating epigenomics,proteomics,and metabolomics for the Chinese population,revealing molecular regulatory networks underlying complex diseases and aiding in disease subtyping and early diagnostic biomarker development.Learning from transnational collaborative research mechanisms,establishing multi-ethnic and multi-regional natural population cohorts in China will systematically dissect the impact of gene-environment interactions on health,providing a scientific basis for localized disease prevention strategies.
作者
王淳
甘丽祯
任贺
方艺
高梓珊
吴云川
Wang Chun;Gan Lizhen;Ren He;Fang Yi;Gao Zishan;Wu Yunchuan(School of Acupuncture-Moxibustion and Tuina,and School of Health Preservation and Rehabilitation,Nanjing University of Chinese Medicine,Nanjing 210046,Jiangsu Province,China)
出处
《中国组织工程研究》
北大核心
2026年第25期6669-6679,共11页
Chinese Journal of Tissue Engineering Research
基金
国家自然科学基金项目(81973941),项目负责人:高梓珊
江苏省卫生健康委员会项目(LKM2023030),项目负责人:吴云川。
关键词
循环炎症蛋白
免疫细胞
类风湿关节炎
孟德尔随机化
逆方差加权法
因果关系
中介分析
芬兰数据库
circulating inflammatory proteins
immune cells
rheumatoid arthritis
Mendelian randomization
inverse variance weighted
causality
mediation analysis
FinnGen database
