Exploring the causal relationship between extensive perivascular space burden and ischemic stroke and its subtypes and transient ischemic attack based on Mendelian randomization
10.3969/j.issn.1006-7795.2025.01.005
- VernacularTitle:基于孟德尔随机化探索广泛的血管周围间隙负荷与缺血性卒中及其亚型和短暂性脑缺血发作的因果关系
- Author:
Xuehong CHU
1
;
Yingjie SHEN
;
Yaolou WANG
;
Xiao DONG
;
Yuanyuan LIU
;
Yan FENG
;
Miaowen JIANG
;
Ming LI
;
Xunming JI
;
Chuanjie WU
Author Information
1. 首都医科大学宣武医院神经内科,北京 100053
- Publication Type:Journal Article
- Keywords:
extensive perivascular space burden;
ischemic stroke;
causal relationship;
Mendelian randomization
- From:
Journal of Capital Medical University
2025;46(1):22-33
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the association between extensive perivascular space(EPVS)burden in different locations and ischemic stroke(IS),its subtypes,and transient ischemic attack(TIA)through Mendelian randomization(MR)analysis.Methods The summary data from large-scale Genome-wide Association Studies(GWAS)and various MR methods were employed.We applied multivariable MR to mitigate potential confounding factors and conduct sensitivity analyses to enhance result robustness.Subsequently,meta-analysis was utilized to integrate causal relationships between EPVS burden in different locations and IS from various sources.Additionally,reverse MR was employed to observe the impact of various IS types on EPVS burden.Finally,linkage disequilibrium score regression was conducted to assess genetic correlations between exposures and outcomes.Results EPVS burden in both the white matter(OR=1.12,95％CI:1.01-1.25;P=0.04)and basal ganglia(OR=1.57,95％CI:1.30-1.89;P＜0.01)are significant risk factors for IS.EPVS burden in the basal ganglia is also a risk for IS(small-vessel)(OR=4.56,95％CI:2.57-8.27;P=5.95× 10-7).After IS and TIA there seems to be a potential increase in extensive basal ganglia perivascular space burden.Conclusions Extensive white matter perivascular space burden and extensive basal ganglia perivascular space burden may serve as important indicators to predict IS.
