血浆代谢物、免疫细胞与髋骨关节炎的因果推断:GWAS数据欧洲群体资料分析  

Plasma metabolites,immune cells,and hip osteoarthritis:causal inference based on GWAS data from European populations

作　　者：容向宾[1,2] 郑海波[1] 莫学燊 侯坤 曾平 Rong Xiangbin;Zheng Haibo;Mo Xueshen;Hou Kun;Zeng Ping(Guangxi University of Chinese Medicine,Nanning 530222,Guangxi Zhuang Autonomous Region,China;Ruikang Hospital,Guangxi University of Chinese Medicine,Nanning 530011,Guangxi Zhuang Autonomous Region,China;First Affiliated Hospital of Guangxi University of Chinese Medicine,Nanning 530022,Guangxi Zhuang Autonomous Region,China)

机构地区：[1]广西中医药大学,广西壮族自治区南宁市530222 [2]广西中医药大学附属瑞康医院,广西壮族自治区南宁市530011 [3]广西中医药大学第一附属医院,广西壮族自治区南宁市530022

出　　处：《中国组织工程研究》2026年第4期1028-1035,共8页Chinese Journal of Tissue Engineering Research

基　　金：国家自然科学基金项目(82160913),项目负责人:曾平;广西中医药大学博士研究生创新项目(YCBZ2023155),项目负责人:容向宾。

摘　　要：背景:有研究证实,骨关节炎患者体内存在单核细胞、T细胞、B细胞以及自然杀伤细胞(NK细胞)等免疫细胞亚群的功能改变,但具体的调节机制尚不明确。目的:探究血浆代谢物介导下免疫细胞与髋骨关节炎的因果关系。方法:以731种免疫细胞的GWAS(由国际组织维护,无特定国家归属,是遗传关联研究数据重要资源库)数据为暴露,髋骨关节炎的GWAS数据为结局,选用1 400种血浆代谢物为中介因素。以双样本孟德尔随机化方法中逆方差加权法为主,使用贝叶斯加权孟德尔随机化方法对逆方差加权法得到的先验分布、样本数据和权重来计算后验分布,根据后验分布来评估逆方差加权分析结果的准确性和可靠性,以MR_Egger、加权中位数、简单模型、加权模式方法做补充,使用多效性检验和异质性检验确保过程稳健性。使用逆方差加权法分析结果进行后续中介效应分析。结果与结论:(1)逆方差加权法确定了4种免疫细胞与髋骨关节炎强相关,与髋骨关节炎具强相关的代谢物有20种,均无反向因果关系。贝叶斯加权孟德尔随机化分析验证结果提示后验均值与逆方差加权估计值相近,且后验方差较小。最终筛选出1种单核细胞亚型(PDL-1on CD14~-CD16~+)与髋骨关节炎存在因果关系,总效应为-0.047(OR=0.954,95%CI=0.926-0.983),并且在蒜氨酸的中介效应为-0.004(OR=0.939,95%CI=0.902-0.978),占总效应的8.5%,说明蒜氨酸是髋骨关节炎进展的保护因素,在此过程中该代谢物发挥了中介作用。(2)国际数据库和欧洲群体分析数据量较大,对中国生物医学有借鉴意义,能为中国人群相似疾病遗传易感基因研究提供线索,有助于发现特有关联;可借鉴其药物基因组学思路,筛选中国人群药物反应基因,提升个体化用药精准性;可学习其先进高通量技术与统计方法,用于疾病防治研究。BACKGROUND:Some studies have confirmed the changes in the function of immune cell subsets such as monocytes,T cells,B cells,and natural killer cells(NK cells)in patients with osteoarthritis,but the specific regulatory mechanisms are unclear.OBJECTIVE:To explore the causal relationship between plasma metabolite-mediated immune cells and hip osteoarthritis.METHODS:The Genome-Wide Association Studies(GWAS)data of 731 immune cells were used as the exposure,the GWAS data of hip osteoarthritis were used as the outcome,and 1400 plasma metabolites were selected as mediating factors.The GWAS database is an important database for genetic association studies,maintained by international organizations with no country-specific affiliation.The inverse variance weighting method in the two-sample Mendelian randomization method was the main method,and the Bayesian weighted Mendelian randomization method was used to analyze the prior distribution,sample data and weights,which were then used to calculate the posterior distribution.The accuracy and reliability of the inverse variance weighting results were evaluated according to the posterior distribution,supplemented by MR-Egger,weighted median,simple model,and weighted mode methods.The pliotropy test and heterogeneity test were used to ensure the robustness of the process.The results of the inverse variance weighting method were used for subsequent mediating effect analysis.RESULTS AND CONCLUSION:(1)The inverse variance weighting method identified 4 immune cells strongly correlated with hip osteoarthritis,and 20 metabolites strongly associated with hip osteoarthritis,all of which had no reverse causal relationship.At the same time,the validation results of Bayesian weighted Mendelian randomization method showed that the posterior mean value was similar to the estimated value of the inverse variance weighting,and the posterior variance was relatively lower.One monocyte subtype(PDL-1 on CD14-CD16+)was finally screened out to have a causal relationship with hip osteoarthritis,with a t

关 键 词：免疫细胞 血浆代谢物 髋骨关节炎 双样本孟德尔随机化分析 中介分析 工程化组织构建 

分 类 号：R459.9[医药卫生—治疗学] R319[医药卫生—临床医学] R684.3