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基于核磁共振的不稳定型心绞痛患者血浆代谢谱分析

NMR-based plasma metabolic profiling in patients with unstable angina.

作者信息

PouralijanAmiri Mohammad, Khoshkam Maryam, Madadi Reza, Kamali Koorosh, Faghanzadeh Ganji Ghassem, Salek Reza, Ramazani Ali

机构信息

Department of Genetics & Molecular Medicine, Faculty of Medicine, Zanjan University of Medical Sciences, Zanjan, Iran.

Chemistry Group, Faculty of Basic Sciences, University of Mohaghegh Ardabili, Ardabil, Iran.

出版信息

Iran J Basic Med Sci. 2020 Mar;23(3):311-320. doi: 10.22038/IJBMS.2020.39979.9475.

Abstract

OBJECTIVES

Unstable angina (UA) is a form of the acute coronary syndrome (ACS) that affects more than a third of the population before age 70. Due to the limitations of diagnostic tests, appropriate identification of UA is difficult. In this study, we proceeded to investigate metabolite profiling in UA patients compared with controls to determine potential candidate biomarkers.

MATERIALS AND METHODS

Ninety-four plasma samples from UA and 32 samples from controls were analyzed based on 1H NMR spectroscopy. The raw data were processed, analyzed, and subjected to partial least squares-discrimination analysis (PLS-DA), a supervised classification method with a good separation of control and UA patients was observed. The most important variables (VIP) ≥1 were selected and submitted to MetaboAnalyst pathway enrichment to identify the most important ones.

RESULTS

We identified 17 disturbed metabolites in UA patients in comparison with the controls. These metabolites are involved in various biochemical pathways such as steroid hormone biosynthesis, aminoacyl-tRNA biosynthesis, and lysine degradation. Some of the metabolites were deoxycorticosterone, 17-hydroxyprogesterone, androstenedione, androstanedione, etiocholanolone, estradiol, 2-hydroxyestradiol, 2-hydroxyestrone, 2-methoxyestradiol, and 2-methoxyestrone. In order to determine test applicability in diagnosing UA, a diagnostic model was further created using the receiver operator characteristic (ROC) curve. The areas under the curve (AUC), sensitivity, specificity, and precision were 0.87, 90%, 65%, and 91%, respectively, for diagnosing of UA.

CONCLUSION

These metabolites could not only be useful for the diagnosis of UA patients but also provide more information for further deciphering of the biological processes of UA.

摘要

目的

不稳定型心绞痛(UA)是急性冠状动脉综合征(ACS)的一种形式,在70岁之前影响超过三分之一的人群。由于诊断测试的局限性,难以对UA进行准确识别。在本研究中,我们对UA患者与对照组进行代谢物谱分析,以确定潜在的候选生物标志物。

材料与方法

基于1H核磁共振波谱分析了94份UA患者的血浆样本和32份对照组样本。对原始数据进行处理、分析,并进行偏最小二乘判别分析(PLS-DA),观察到一种能很好区分对照组和UA患者的监督分类方法。选择重要性变量(VIP)≥1的变量,并提交给MetaboAnalyst进行通路富集分析,以确定最重要的变量。

结果

与对照组相比,我们在UA患者中鉴定出17种代谢紊乱的代谢物。这些代谢物参与各种生化途径,如类固醇激素生物合成、氨酰-tRNA生物合成和赖氨酸降解。其中一些代谢物是脱氧皮质酮、17-羟孕酮、雄烯二酮、雄烷二酮、本胆烷醇酮、雌二醇、2-羟雌二醇、2-羟雌酮、2-甲氧基雌二醇和2-甲氧基雌酮。为了确定该测试在诊断UA中的适用性,使用受试者工作特征(ROC)曲线进一步创建了诊断模型。诊断UA的曲线下面积(AUC)、敏感性、特异性和精确度分别为0.87、90%、65%和91%。

结论

这些代谢物不仅有助于UA患者的诊断,还能为进一步解读UA的生物学过程提供更多信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d18/7229510/071ee226d6e9/IJBMS-23-311-g001.jpg

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