Improvement of myocardial infarction risk prediction via inflammation-associated metabolite biomarkers

医学 代谢物 内科学 代谢组学 心肌梗塞 弗雷明翰风险评分 前瞻性队列研究 炎症 C反应蛋白 接收机工作特性 全身炎症 生物标志物 心脏病学 生物信息学 疾病 生物化学 生物
作者
Cavin Ward‐Caviness,Tao Xu,Thor Aspelund,Barbara Thorand,Corinna Montrone,Christa Meisinger,Irmtraud Dunger-Kaltenbach,Astrid Zierer,Zhonghao Yu,Inga R Helgadottir,Tamara B. Harris,Lenore J. Launer,Andrea Ganna,Lars Lind,Guðný Eiríksdóttir,Mélanie Waldenberger,Cornelia Prehn,Karsten Suhre,Thomas Illig,Jerzy Adamski,Andreas Ruepp,Wolfgang Köenig,Vilmundur Guðnason,Valur Emilsson,Rui Wang‐Sattler,Annette Peters
出处
期刊:Heart [BMJ]
卷期号:103 (16): 1278-1285 被引量:42
标识
DOI:10.1136/heartjnl-2016-310789
摘要

Objective

The comprehensive assaying of low-molecular-weight compounds, for example, metabolomics, provides a unique tool to uncover novel biomarkers and understand pathways underlying myocardial infarction (MI). We used a targeted metabolomics approach to identify biomarkers for MI and evaluate their involvement in the pathogenesis of MI.

Methods and results

Using three independent, prospective cohorts (KORA S4, KORA S2 and AGES-REFINE), totalling 2257 participants without a history of MI at baseline, we identified metabolites associated with incident MI (266 cases). We also investigated the association between the metabolites and high-sensitivity C reactive protein (hsCRP) to understand the relation between these metabolites and systemic inflammation. Out of 140 metabolites, 16 were nominally associated (p<0.05) with incident MI in KORA S4. Three metabolites, arginine and two lysophosphatidylcholines (LPC 17:0 and LPC 18:2), were selected as biomarkers via a backward stepwise selection procedure in the KORA S4 and were significant (p<0.0003) in a meta-analysis comprising all three studies including KORA S2 and AGES-REFINE. Furthermore, these three metabolites increased the predictive value of the Framingham risk score, increasing the area under the receiver operating characteristic score in KORA S4 (from 0.70 to 0.78, p=0.001) and AGES-REFINE study (from 0.70 to 0.76, p=0.02), but was not observed in KORA S2. The metabolite biomarkers attenuated the association between hsCRP and MI, indicating a potential link to systemic inflammatory processes.

Conclusions

We identified three metabolite biomarkers, which in combination increase the predictive value of the Framingham risk score. The attenuation of the hsCRP–MI association by these three metabolites indicates a potential link to systemic inflammation.
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