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Plasma metabolites, systolic blood pressure, lifestyle and stroke risk: a UK Biobank based cohort study

医学 冲程(发动机) 内科学 血压 比例危险模型 队列 蛛网膜下腔出血 脑出血 心脏病学 机械工程 工程类
作者
Canjia Zhang,Mingxiao Li,Miaomiao Yang,Jiaqi Lin,Jinyao Huang,Ying Lin,Xi Chen,Yongqiang Liang,Yuanhai Yang,Ziyuan Yu,Dongsheng Hu,Ming Zhang,Fulan Hu
出处
期刊:International Journal of Stroke [SAGE Publishing]
标识
DOI:10.1177/17474930241293408
摘要

Background: To estimate the associations of stroke risk with plasma metabolites, metabolic risk score (MRS), the combinations of MRS with hypertension or lifestyle, and lifestyle-related metabolic signature. To assess the improvement of the stroke risk prediction model through the incorporation of MRS. Methods: A total of 77,315 participants from the UK Biobank were included in this study. Xgboost and LASSO-Cox regression were used to select metabolites and construct MRS. Elastic net regression was utilized to construct the lifestyle-related metabolic signature. Multivariate Cox regression was used to estimate the associations between metabolites, MRS, the combinations of MRS with hypertension or lifestyle, lifestyle-related metabolic signature, and stroke risk. Results: We identified 48, 63, 39, and 4 metabolites associated with the risk of stroke, ischemic stroke (IS), subarachnoid hemorrhage (SAH), and intracerebral hemorrhage (ICH), respectively. High MRS significantly increased the risk of stroke (HR = 2.65 (95% confidence interval (CI): 2.09−3.35)), IS (HR = 2.45 (95% CI: 1.89−3.17)), ICH (HR = 2.74 (95% CI: 1.55−4.85)), and SAH (HR = 4.64 (95% CI: 2.25−9.56)). In the combination analyses, compared with normal systolic blood pressure (SBP) and low MRS, normal/high SBP, and high MRS significantly increased stroke risk (HR = 5.80 (95% CI: 2.75–12.27)/6.37 (95% CI: 3.22−12.62)). A favorable/unfavorable lifestyle and high MRS also significantly increased stroke risk (HR = 2.38 (95% CI: 1.73–3.28)/3.86 (95% CI: 2.63−5.67)) compared with a favorable lifestyle and low MRS. Incorporating MRS into the 15-year stroke and IS risk prediction model increased the areas under the curves (AUCs) from 0.746 to 0.766 and from 0.771 to 0.811, respectively. The metabolic signature was correlated with adherence to a healthy lifestyle (r = 0.414; P = 2.22e−16) and inversely associated with stroke risk (HR = 0.80 (95% CI: 0.73–0.86)). Conclusions: Various metabolites and MRS were significantly associated with the risk of stroke, IS, ICH, and SAH. Individuals with a high MRS may face an elevated stroke risk among populations with high SBP or unhealthy lifestyle, even those with normal SBP or healthy lifestyle. MRS provided modest improvement to the stroke risk prediction model. The lifestyle-related metabolic signature could reduce 20% stroke risk.
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