Metabolomic Profiles Associated With Incident Ischemic Stroke

冲程(发动机) 医学 优势比 内科学 代谢物 前瞻性队列研究 逻辑回归 入射(几何)
作者
Raji Balasubramanian,Jie Hu,Marta Guasch-Ferré,Jun Li,Farzaneh A. Sorond,Yibai Zhao,Katherine H. Shutta,Jordi Salas Salvadó,Frank B. Hu,Clary B. Clish,Kathryn M. Rexrode
出处
期刊:Neurology [Lippincott Williams & Wilkins]
卷期号:: 10.1212/WNL.0000000000013129-10.1212/WNL.0000000000013129
标识
DOI:10.1212/wnl.0000000000013129
摘要

Background: Women have higher lifetime risk of stroke than men, and metabolic factors seem more strongly associated with stroke for women than men. However, few studies in either men or women have evaluated metabolomic profiles and incident stroke. Methods: We applied liquid chromatography-tandem mass spectrometry to measure 519 plasma metabolites in a discovery set of women in the Nurses’ Health Study ([NHS], 454 incident ischemic stroke cases, 454 controls) with validation in two independent, prospective cohorts: Prevención con Dieta Mediterránea ([PREDIMED], 118 stroke cases, 791 controls), and Nurses’ Health Study 2 ([NHS2], 49 ischemic stroke cases, 49 controls). We applied logistic regression models with stroke as the outcome to adjust for multiple risk factors; the false discovery rate (FDR) was controlled through the q value method. Results: Twenty-three metabolites were significantly associated with incident stroke in NHS after adjustment for traditional risk factors (q value <0.05). Of these, 14 metabolites were available in PREDIMED and 3 were significantly associated with incident stroke: methionine sulfoxide, N6-acetyllysine, and sucrose (q value<0.05). In NHS2, one of the 23 metabolites (glucuronate) was significantly associated with incident stroke (q value <0.05). For all four metabolites, higher levels were associated with increased risk. These four metabolites were used to create a stroke metabolite score (SMS) in the NHS and tested in PREDIMED. Per unit of standard deviation of SMS, the odds ratio for incident stroke was 4.12 (95% CI: 2.26 – 7.51) in PREDIMED, after adjustment for risk factors. In PREDIMED, the area under the ROC curve (AUC) for the model including SMS and traditional risk factors was 0.70 (95% CI: 0.75-0.79) versus the AUC for the model including the traditional risk factors only of 0.65 (95% CI: 0.70-75), corresponding to a 5% improvement in risk prediction with SMS (p < 0.005). Discussion: Metabolites associated with stroke included two amino acids, a carboxylic acid and sucrose. A composite SMS including these metabolites was associated with ischemic stroke and showed improvement in risk prediction beyond traditional risk factors. Classification of Evidence: This study provides Class II evidence that a stroke metabolic score accurately predicts incident ischemic stroke risk.

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