Bye Anja, Røsjø Helge, Nauman Javaid, Silva Gustavo J J, Follestad Turid, Omland Torbjørn, Wisløff Ulrik
K.G. Jebsen Center of Exercise in Medicine at Dept. of Circulation and Medical Imaging, Faculty of Medicine, Norwegian University of Science and Technology (NTNU), Norway; Department of Cardiology, St. Olavs Hospital, Trondheim, Norway.
Division of Medicine, Akershus University Hospital, Lørenskog, Norway; Center for Heart Failure Research, Institute for Clinical Medicine, University of Oslo, Norway.
J Mol Cell Cardiol. 2016 Aug;97:162-8. doi: 10.1016/j.yjmcc.2016.05.009. Epub 2016 May 15.
Coronary heart disease is the most common cause of death, and the number of individuals at risk is increasing. To better manage this pandemic, improved tool for risk prediction, including more accurate biomarkers are needed. The objective of this study was to assess the utility of circulating microRNAs (miRs) to predict future fatal acute myocardial infarction (AMI) in healthy participants. We performed a prospective nested case-control study with 10-year observation period and fatal AMI as endpoint. In total, 179 miRs were quantified by real-time polymerase chain reaction in serum of 112 healthy participants (40-70years) that either (1) suffered from fatal AMI within 10years [n=56], or (2) remained healthy [n=56, risk factor-matched controls]. Candidate miRs were validated in a separate cohort of healthy individuals (n=100). Twelve miRs were differently expressed in cases and controls in the derivation cohort (p<0.05). Among these, 10 miRs differed significantly between cases and controls in the validation cohort (p<0.05). We identified gender dimorphisms, as miR-424-5p and miR-26a-5p were associated exclusively with risk in men and women, respectively. The best model for predicting future AMI consisted of miR-106a-5p, miR-424-5p, let-7g-5p, miR-144-3p and miR-660-5p, providing 77.6% correct classification for both genders, and 74.1% and 81.8% for men and women, respectively. Adding these 5 miRs to the Framingham Risk Score, increased the AUC from 0.72 to 0.91 (p<0.001). In conclusion, we identified several miRs associated with future AMI, revealed gender-specific associations, and proposed a panel of 5 miRs to enhance AMI risk prediction in healthy individuals.
冠心病是最常见的死亡原因，且高危人群数量正在增加。为了更好地应对这一流行病，需要改进风险预测工具，包括更准确的生物标志物。本研究的目的是评估循环微RNA（miR）在预测健康参与者未来致命性急性心肌梗死（AMI）方面的效用。我们进行了一项前瞻性巢式病例对照研究，观察期为10年，以致命性AMI为终点。总共对112名健康参与者（40 - 70岁）的血清进行了实时聚合酶链反应，定量检测了179种miR，这些参与者分为两类：（1）在10年内发生致命性AMI的[ n = 56 ]，或（2）保持健康的[ n = 56，风险因素匹配的对照组]。候选miR在另一组健康个体（n = 100）中进行了验证。在推导队列中，12种miR在病例组和对照组中表达不同（p < 0.05）。其中，10种miR在验证队列的病例组和对照组之间有显著差异（p < 0.05）。我们发现了性别差异，因为miR - 424 - 5p和miR - 26a - 5p分别仅与男性和女性的风险相关。预测未来AMI的最佳模型由miR - 106a - 5p、miR - 424 - 5p、let - 7g - 5p、miR - 144 - 3p和miR - 660 - 5p组成，对男女的正确分类率均为77.6%，对男性和女性分别为74.1%和81.8%。将这5种miR添加到弗明汉风险评分中，曲线下面积从0.72增加到0.91（p < 0.001）。总之，我们鉴定了几种与未来AMI相关的miR，揭示了性别特异性关联，并提出了一个由5种miR组成的组合，以增强对健康个体的AMI风险预测。
