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非靶向高分辨血浆代谢组学分析预测冠心病患者的结局。

Untargeted high-resolution plasma metabolomic profiling predicts outcomes in patients with coronary artery disease.

机构信息

Emory Clinical Cardiovascular Research Institute, Division of Cardiology, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia.

Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia.

出版信息

PLoS One. 2020 Aug 18;15(8):e0237579. doi: 10.1371/journal.pone.0237579. eCollection 2020.


DOI:10.1371/journal.pone.0237579
PMID:32810196
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7444579/
Abstract

OBJECTIVE: Patients with CAD have substantial residual risk of mortality, and whether hitherto unknown small-molecule metabolites and metabolic pathways contribute to this risk is unclear. We sought to determine the predictive value of plasma metabolomic profiling in patients with CAD. APPROACH AND RESULTS: Untargeted high-resolution plasma metabolomic profiling of subjects undergoing coronary angiography was performed using liquid chromatography/mass spectrometry. Metabolic features and pathways associated with mortality were identified in 454 subjects using metabolome-wide association studies and Mummichog, respectively, and validated in 322 subjects. A metabolomic risk score comprising of log-transformed HR estimates of metabolites that associated with mortality and passed LASSO regression was created and its performance validated. In 776 subjects (66.8 years, 64% male, 17% Black), 433 and 357 features associated with mortality (FDR-adjusted q<0.20); and clustered into 21 and 9 metabolic pathways in first and second cohorts, respectively. Six pathways (urea cycle/amino group, tryptophan, aspartate/asparagine, lysine, tyrosine, and carnitine shuttle) were common. A metabolomic risk score comprising of 7 metabolites independently predicted mortality in the second cohort (HR per 1-unit increase 2.14, 95%CI 1.62, 2.83). Adding the score to a model of clinical predictors improved risk discrimination (delta C-statistic 0.039, 95%CI -0.006, 0.086; and Integrated Discrimination Index 0.084, 95%CI 0.030, 0.151) and reclassification (continuous Net Reclassification Index 23.3%, 95%CI 7.9%, 38.2%). CONCLUSIONS: Differential regulation of six metabolic pathways involved in myocardial energetics and systemic inflammation is independently associated with mortality in patients with CAD. A novel risk score consisting of representative metabolites is highly predictive of mortality.

摘要

目的:患有 CAD 的患者有大量的死亡残余风险,目前尚不清楚是否存在以前未知的小分子代谢物和代谢途径对此风险有贡献。我们试图确定 CAD 患者血浆代谢组谱分析的预测价值。

方法和结果:对接受冠状动脉造影的患者进行了非靶向高分辨率血浆代谢组学分析,使用液相色谱/质谱法。通过代谢组学全基因组关联研究和 Mummichog 分别在 454 例患者中确定了与死亡率相关的代谢特征和途径,并在 322 例患者中进行了验证。创建了一个包含与死亡率相关且通过 LASSO 回归的代谢物的对数变换 HR 估计的代谢风险评分,并验证了其性能。在 776 例患者(66.8 岁,64%为男性,17%为黑人)中,第一和第二队列中分别有 433 个和 357 个特征与死亡率相关(FDR 调整的 q<0.20);并分别聚类成 21 个和 9 个代谢途径。六个途径(尿素循环/氨基组、色氨酸、天冬氨酸/天冬酰胺、赖氨酸、酪氨酸和肉碱穿梭)是常见的。由 7 种代谢物组成的代谢风险评分可独立预测第二队列的死亡率(每增加 1 单位的 HR 为 2.14,95%CI 为 1.62 至 2.83)。将评分添加到临床预测因子模型中可提高风险区分度(增量 C 统计量为 0.039,95%CI -0.006,0.086;和综合判别指数为 0.084,95%CI 0.030,0.151)和重新分类(连续净重新分类指数为 23.3%,95%CI 为 7.9%,38.2%)。

结论:涉及心肌能量和全身炎症的六个代谢途径的差异调节与 CAD 患者的死亡率独立相关。由代表性代谢物组成的新型风险评分对死亡率具有高度预测性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffb2/7444579/1ff9a79b4185/pone.0237579.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffb2/7444579/fbc97fcc5cd1/pone.0237579.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffb2/7444579/95fbad7729e9/pone.0237579.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffb2/7444579/1ff9a79b4185/pone.0237579.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffb2/7444579/fbc97fcc5cd1/pone.0237579.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffb2/7444579/95fbad7729e9/pone.0237579.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffb2/7444579/1ff9a79b4185/pone.0237579.g003.jpg

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本文引用的文献

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