The Impact of Conventional Stroke Risk Factors on Early and Late Onset Ischemic Stroke: a Mendelian Randomization Study

孟德尔随机化 冲程(发动机) 医学 入射(几何) 缺血性中风 随机化 中风风险 儿科 内科学 心脏病学 随机对照试验 缺血 遗传变异 基因 机械工程 基因型 工程类 生物化学 化学 物理 光学
作者
Kevin T.K. Nguyen,Huichun Xu,Brady Gaynor,Sally N. Adebamowo,Patrick F. McArdle,Tim O’Connor,Bradford B. Worrall,Rainer Malik,Giorgio B. Boncoraglio,Ramin Zand,Steven J. Kittner,Braxton D. Mitchell
出处
期刊:Cold Spring Harbor Laboratory - medRxiv
标识
DOI:10.1101/2024.05.31.24308308
摘要

Abstract Objective Although stroke incidence is decreasing in older ages, it is increasing in young adults. While these divergent trends in stroke incidence are at least partially attributable to diverging prevalence trends in stoke risk factors, age-dependent differences in the impact of stroke risk factors on stroke may also contribute. To address this issue, we utilized Mendelian Randomization (MR) to assess differences in the association of stroke risk factors between early onset ischemic stroke (EOS) and late onset ischemic stroke (LOS). Methods We employed a two-sample MR design with inverse variance weighting as the primary method of analysis. Using large publicly available genome-wide association summary results, we calculated MR estimates for conventional stroke risk factors (body mass index, total, HDL-and LDL-cholesterol, triglycerides, type 2 diabetes, systolic and diastolic blood pressure, and smoking) in EOS cases (onset 18-59 years, n = 6,728) and controls from the Early Onset Stroke Consortium and in LOS cases (onset ≥ 60 years, n = 9,272) and controls from the Stroke Genetics Network. We then compared odds ratios between EOS and LOS, stratified by TOAST subtypes, to determine if any differences observed between effect sizes could be attributed to differences in the distribution of stroke subtypes. Results EOS was significantly associated with all risk factors except for total cholesterol levels, and LOS was associated with all risk factors except for triglyceride and total cholesterol levels. The associations of BMI, DBP, SBP, and HDL-cholesterol were significantly stronger in EOS than LOS (all p < 0.004). The differential distribution of stroke subtypes could not explain the difference in effect size observed between EOS and LOS. Conclusion These results suggest that interventions targeted at lowering body mass index and blood pressure may be particularly important for reducing stroke risk in young adults.

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