摘要
目的 通过孟德尔随机化分析方法,探讨炎性细胞因子与纤维肌痛症之间的因果关联.方法 通过对GWAS Catalog数据库与FinnGen数据库进行挖掘,设置暴露因素为炎症细胞因子,结局为纤维肌痛症.主要采用逆方差加权法(IVW)进行分析,MR-Egger、简单中位数法(Simple Mode)法、加权中位数法(WM)和加权中值方法(Weighted Mode)等统计方法作为补充进行孟德尔随机化分析.随后通过调换暴露因素与结局,检验分析的方向性.结果 在91种已知炎症细胞因子中,发现自然杀伤细胞受体2B4(CD244)、单细胞趋化蛋白2(MCP-2)、C-X-C趋化因子6(CXCL6)、IL-12β亚单位(IL-12B)与纤维肌痛症之间存在因果关联,CD244[OR值(95％CI):1.21(1.08,1.35),P＜0.001],MCP-2[OR 值(95％CI):0.91(0.87,0.96),P＜0.001],CXCL6[OR 值(95％CI):1.15(1.06,1.24),P＜0.001],IL-12B[OR值(95％CI)=1.13(1.06,1.20),P＜0.001].敏感性分析中未发现分析结果存在多效性、异质性以及弱相关性.结论 CD244、CXCL 6和IL-12B的水平升高会增加FM的疾病风险,而MCP-2水平的升高则会降低FM的疾病风险.
Abstract
Objective To explore the causal association between inflammatory cytokines and fibromyalgia by Mendelian randomization analysis.Methods By mining the GWAS Catalog database and FinnGen database,the exposure factor was set as inflammatory cytokines,and the outcome was fibromyalgia.The main analysis method adopted in this study is inverse variance weighted(IVW)method,with MR-Egger,Simple Mode method,weighted median(WM),and Weighted Mode as supplementary statistical methods for Mendelian randomization analysis.Subsequently,by swapping the exposure factors and outcomes,the directionality of the analysis was tested.Results Among the 91 known inflammatory cytokines,a causal association was found between natural killer cell receptor 2B4(CD244),monocyte chemotactic protein 2(MCP-2),C-X-C chemokine 6(CXCL6),interleukin 12β subunit(IL12B),and fibromyalgia.Among them,CD244,CXCL6,and IL12B were positively correlated with FM[CD244:OR(95％CI)=1.21(1.08,1.35),P＜0.001].[MCP-2:OR(95％CI)=0.91(0.87,0.96),P＜0.001],[CXCL6:OR(95％CI)=1.15(1.06,1.24),P＜0.001],IL-12B[OR(95％CI)=1.13(1.06,1.20),P＜0.001].Sensitivity analysis did not find multiple effects,heterogeneity,or correlation.Conclusion The increase in the levels of CD244,CXCL6,and IL-12B will increase the risk of FM,while the increase in the level of MCP-2 will reduce the risk of FM disease.
基金项目
广西中医药大学桂派中医药传承项目(2022V001)
中医药人才队伍建设专项(20230170508)
广西中医药大学自治区级硕士研究生科研创新项目(YCSW2023375)
NETL
NSTL
万方数据