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Author Spotlight: Assessing Ischemic Stroke Damage Through Middle Cerebral Artery Occlusion Model
Published on: August 11, 2023
The effect of hypertension, obesity, and type 2 diabetes on lacunar stroke: A network Mendelian randomization study
Zhi-Ping Wu1, Wei Wei2, Shan Liu3
1Department of Epidemiology, School of Public Health, Dalian Medical University, Dalian, China.
Background And Aims:
Previous studies have reported an association of lacunar stroke with hypertension, obesity, and type 2 diabetes (T2D). The aim of this study was to investigate whether the association was causal and whether body mass index mediated the effect of hypertension on lacunar stroke.
Methods And Results:
The independence and causal association of hypertension, obesity, and T2D with lacunar stroke were assessed by multivariate Mendelian randomization (MVMR) and network Mendelian randomization (NMR) with inverse variance weighting (IVW). The reliability of the results was increased by sensitivity analyses including MR-Egger, Cochrane's Q test, Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO), and leave-one-out. MVMR analysis found that genetically predicted hypertension had a 42 % higher lacunar stroke risk (OR: 1.42, 95 % CI: 1.29-1.56, P < 0.001) when adjusted for obesity and T2D, genetically predicted T2D had a 9 % higher lacunar stroke risk (OR: 1.09, 95 % CI: 1.03-1.16, P < 0.004) when adjusted for hypertension and obesity, and genetically predicted obesity had a 15 % lower lacunar stroke risk (OR: 0.85, 95 % CI: 0.77-0.93, P < 0.001) when adjusted for hypertension and T2D. NMR found that 44 % of the association between hypertension and lacunar stroke risk was mediated by obesity.
Conclusion:
This genetic association study found novel independent genetic associations between hypertension and T2D with high risk of lacunar stroke, whereas obesity attenuated the risk of lacunar stroke. The findings emphasize the importance of individualized lacunar stroke prevention strategies rather than uniform weight management optimize medical care in high-risk populations.
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