摘要
目的 探讨骨关节炎与阿尔茨海默病之间的关系。方法 从全基因组关联研究(GWAS)汇总统计中获取骨关节炎和阿尔茨海默病的数据。采用严格的筛选步骤筛选合格的工具变量,采用逆方差加权法(IVW)为主要方法并结合加权中位数、MR-Egger回归以及加权模式方法进行双向孟德尔随机化分析。为确保结果的稳健性,采用MR-Egger截距检验、Cochran's Q检验和留一法分析三种敏感性分析来评估多效性和异质性。结果 IVW分析结果显示,骨关节炎的遗传易感性和阿尔茨海默病的发病风险存在因果效应(OR=19.887,95%CI:2.896~136.568,P=0.002);而阿尔茨海默病的遗传易感性与骨关节炎发病风险无相关性(OR=1.001,95%CI:0.999~1.003,P=0.422)。结论 骨关节炎能够增加阿尔茨海默病发生的风险,而阿尔茨海默病不能增加骨关节炎的发病风险。
Objective To investigate the possible causal relationship between osteoarthritis and Alzheimer's dis⁃ease.Methods Data on osteoarthritis and Alzheimer's disease were obtained from the Genome-Wide Association Studies summary statistics.Use the bidirectional Mendelian randomization analysis,strictly screen the instrumental variables,and the inverse variance weighting method(IVW)was used as the main method,combined with weighted median,MR-Egger regression and weighted model method for analysis.To ensure the robustness of the results,three sensitivity analyses in⁃cluding MR-Egger intercept test,Cochran's Q test and leave-one-out analysis were used to assess pleiotropy and heterogene⁃ity.Results IVW analysis showed that there was a causal effect between genetic susceptibility to osteoarthritis and risk of Alzheimer's disease(OR=19.887,95%CI:2.896-136.568,P=0.002).However,there was no correlation between genetic susceptibility to Alzheimer disease and the risk of osteoarthritis(OR=1.001,95%CI:0.999-1.003,P=0.422).Conclusion Osteoarthritis can increase the risk of developing Alzheimer's disease,and Alzheimer's disease does not in⁃crease the risk of developing osteoarthritis.
作者
段圆圆
饶泽辉
邹志明
DUAN Yuanyuan;RAO Zehui;ZOU Zhiming(School of Intelligent Technology,Jiangxi Open University,Nanchang 330046,China;The First Clinical Medical College of Nanchang University,Nanchang 330006,China;Electrocardiogram Room of Nanchang First Hospital,Nanchang 330000,China)
出处
《老年医学研究》
2024年第5期28-32,共5页
Geriatrics Research
关键词
骨关节炎
阿尔茨海默病
孟德尔随机化
全基因组关联研究
逆方差加权法
osteoarthritis
Alzheimer's disease
Mendelian randomization
genome-wide association analysis
in⁃verse variance weighting