From the Human Genetics Center, University of Texas Health Science Center at Houston (Z.W., C.Z., A.C.M., E.B., B.Y.).
Michael E. Debakey Veterans Affairs Hospital, Houston, TX (V.N.).
Arterioscler Thromb Vasc Biol. 2019 Jul;39(7):1475-1482. doi: 10.1161/ATVBAHA.118.312236. Epub 2019 May 16.
Objective- Alterations in the serum metabolome may be detectable in at-risk individuals before the onset of coronary heart disease (CHD). Identifying metabolomic signatures associated with CHD may provide insight into disease pathophysiology and prevention. Approach and Results- Metabolomic profiling (chromatography-mass spectrometry) was performed in 2232 African Americans and 1366 European Americans from the ARIC study (Atherosclerosis Risk in Communities). We applied Cox regression with least absolute shrinkage and selection operator to select metabolites associated with incident CHD. A metabolite risk score was constructed to evaluate whether the metabolite risk score predicted CHD risk beyond traditional risk factors. After 30 years of follow-up, we observed 633 incident CHD cases. Thirty-two metabolites were selected by least absolute shrinkage and selection operator to be associated with CHD, and 19 of the 32 showed significant individual associations with CHD, including a sugar substitute, erythritol. Theophylline (hazard ratio [95% CI] =1.16 [1.09-1.25]) and gamma-linolenic acid (hazard ratio [95% CI] =0.89 [0.81-0.97]) showed the greatest positive and negative associations with CHD, respectively. A 1 SD greater standardized metabolite risk score was associated with a 1.37-fold higher risk of CHD (hazard ratio [95% CI] =1.37 [1.27-1.47]). Adding the metabolite risk score to the traditional risk factors significantly improved model predictive performance (30-year risk prediction: Δ C statistics [95% CI] =0.016 [0.008-0.024], continuous net reclassification index [95% CI] =0.522 [0.480-0.556], integrated discrimination index [95% CI] =0.038 [0.019-0.065]). Conclusions- We identified 19 metabolites from known and novel metabolic pathways that collectively improved CHD risk prediction. Visual Overview- An online visual overview is available for this article.
目的- 在冠心病（CHD）发作前，高危人群的血清代谢组可能会发生变化。确定与 CHD 相关的代谢组学特征可能有助于深入了解疾病的病理生理学和预防。方法和结果- 在 ARIC 研究（社区动脉粥样硬化风险）中，对 2232 名非裔美国人和 1366 名欧洲裔美国人进行了代谢组学分析（色谱-质谱）。我们应用 Cox 回归最小绝对收缩和选择算子选择与 CHD 事件相关的代谢物。构建代谢物风险评分，以评估代谢物风险评分是否可以在传统危险因素之外预测 CHD 风险。经过 30 年的随访，我们观察到 633 例 CHD 事件。最小绝对收缩和选择算子选择了 32 种与 CHD 相关的代谢物，其中 19 种代谢物与 CHD 呈显著个体相关性，包括一种糖替代品赤藓糖醇。茶碱（危险比[95%置信区间] =1.16[1.09-1.25]）和γ-亚麻酸（危险比[95%置信区间] =0.89[0.81-0.97]）与 CHD 的相关性最强。标准化代谢物风险评分每增加 1 个标准差，CHD 风险增加 1.37 倍（危险比[95%置信区间] =1.37[1.27-1.47]）。将代谢物风险评分添加到传统危险因素中，显著提高了模型预测性能（30 年风险预测：Δ C 统计量[95%置信区间] =0.016[0.008-0.024]，连续净重新分类指数[95%置信区间] =0.522[0.480-0.556]，综合判别指数[95%置信区间] =0.038[0.019-0.065]）。结论- 我们从已知和新的代谢途径中确定了 19 种代谢物，这些代谢物共同提高了 CHD 风险预测。可视化概述- 本文提供了在线可视化概述。
