基于孟德尔随机化的COVID-19重症与迟发性重症肌无力的关系研究  

Study on relationship between severe COVID-19 and delayed onset myasthenia gravis based on Mendelian randomization

作　　者：张小凤 车明璐 阳李 张春青 ZHANG Xiaofeng;CHE Minglu;YANG Li;ZHANG Chunqing(Department of Neurosurgery,the Second Affiliated Hospital of Army Medical University,Chongqing 400037,China)

机构地区：[1]陆军军医大学第二附属医院神经外科,重庆400037

出　　处：《重庆医学》2024年第21期3228-3232,3239,共6页Chongqing Medical Journal

基　　金：重庆科卫联合中青年高端人才项目(2024GDRC013)。

摘　　要：目的基于孟德尔随机化(MR)探讨新型冠状病毒感染(COVID-19)易感、住院、重症与迟发性重症肌无力(LOMG)之间潜在的因果关系。方法筛选非重叠全基因组关联研究公开数据,将COVID-19易感、住院、重症作为暴露数据,LOMG作为结局数据,主要采用逆方差加权法(IVW)评估因果效应,辅以MR-Egger法、加权中位数法、加权模型、简单模型等方法,并进行敏感性分析。结果遗传预测的COVID-19重症与LOMG(OR=1.01,95%CI=1.00~1.03,P=0.046)呈正向因果关系。敏感性分析结果显示,该研究结果稳健(P>0.05),未发现异质性或水平多效性。结论COVID-19重症可能与LOMG风险增加有关。Objective To investigate the potential causal relationships between coronavirus disease-2019(COVID-19)susceptibility,hospitalization and severe case with late-onset myasthenia gravis(LOMG)based on Mendelian randomization(MR).Methods The public data from non-overlapping genome-wide association studies were screened,COVID-19 susceptibility,hospitalization and severe case served as the exposure data,and LOMG as the outcome data.The inverse-variance weighted(IVW)method was mainly adopted to evaluate the causal effect,which was supplemented by the methods such as MR-Egger method,weighted median method,weighted model and simple model.The sensitivity analysis was performed.Results The genetically predicted severe case of COVID-19 had the positively causal relationship with LOMG(OR=1.01,95%CI:1.00-1.03,P=0.046).The sensitivity analysis results revealed the study results were steady(P>0.05).No heterogeneity or horizontal pleiotropy was found.Conclusion Severe case of COVID-19 may be associated with an increased risk of LOMG.

关 键 词：新型冠状病毒感染 迟发型重症肌无力 孟德尔随机化 全基因组关联研究 敏感性分析 

分 类 号：R511[医药卫生—内科学]