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本文引用的文献

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Small Things Matter: Relevance of MicroRNAs in Cardiovascular Disease.小事物亦重要:微小RNA在心血管疾病中的相关性
Front Physiol. 2020 Jul 7;11:793. doi: 10.3389/fphys.2020.00793. eCollection 2020.
2
An update on genetic risk scores for coronary artery disease: are they useful for predicting disease risk and guiding clinical decisions?冠状动脉疾病遗传风险评分的最新进展:它们对预测疾病风险和指导临床决策有用吗?
Expert Rev Cardiovasc Ther. 2020 Aug;18(8):443-447. doi: 10.1080/14779072.2020.1797489. Epub 2020 Aug 9.
3
Macrophage polarisation associated with atherosclerosis differentially affects their capacity to handle lipids.动脉粥样硬化相关的巨噬细胞极化状态会对其处理脂质的能力产生差异影响。
Atherosclerosis. 2020 Jul;305:10-18. doi: 10.1016/j.atherosclerosis.2020.05.003. Epub 2020 Jun 10.
4
Non-obstructive high-risk plaques increase the risk of future culprit lesions comparable to obstructive plaques without high-risk features: the ICONIC study.非阻塞性高危斑块增加未来罪犯病变的风险,与无高危特征的阻塞性斑块相当:ICONIC研究。
Eur Heart J Cardiovasc Imaging. 2020 Sep 1;21(9):973-980. doi: 10.1093/ehjci/jeaa048.
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Predictive Accuracy of a Polygenic Risk Score Compared With a Clinical Risk Score for Incident Coronary Heart Disease.多基因风险评分与临床风险评分预测冠心病事件的准确性比较。
JAMA. 2020 Feb 18;323(7):627-635. doi: 10.1001/jama.2019.21782.
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Heart Disease and Stroke Statistics-2020 Update: A Report From the American Heart Association.《心脏病与卒中统计-2020 更新:来自美国心脏协会的报告》。
Circulation. 2020 Mar 3;141(9):e139-e596. doi: 10.1161/CIR.0000000000000757. Epub 2020 Jan 29.
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F-Sodium Fluoride Positron Emission Tomography/Computed Tomography in Ex Vivo Human Coronary Arteries With Histological Correlation.F-氟化钠正电子发射断层扫描/计算机断层扫描与组织学相关性的离体人冠状动脉。
Arterioscler Thromb Vasc Biol. 2020 Feb;40(2):404-411. doi: 10.1161/ATVBAHA.119.312737. Epub 2019 Dec 26.
8
Plasma protein patterns as comprehensive indicators of health.血浆蛋白质谱作为全面的健康指标。
Nat Med. 2019 Dec;25(12):1851-1857. doi: 10.1038/s41591-019-0665-2. Epub 2019 Dec 2.
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Comparative Transcriptomics of , Patient-Derived Endothelial Cells Reveals Novel Pathways Associated With Type 2 Diabetes Mellitus.患者来源的内皮细胞的比较转录组学揭示了与2型糖尿病相关的新途径。
JACC Basic Transl Sci. 2019 Sep 23;4(5):567-574. doi: 10.1016/j.jacbts.2019.05.012. eCollection 2019 Sep.
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Machine learning reveals serum sphingolipids as cholesterol-independent biomarkers of coronary artery disease.机器学习揭示血清神经酰胺为独立于胆固醇的冠心病生物标志物。
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预测动脉粥样硬化性心血管疾病风险的分子基础。

The Molecular Basis of Predicting Atherosclerotic Cardiovascular Disease Risk.

机构信息

Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston (M.N., K.J.B.).

Sections of Preventive Medicine & Epidemiology, and Cardiology, Department of Medicine, Boston University School of Medicine, MA (R.S.V.).

出版信息

Circ Res. 2021 Jan 22;128(2):287-303. doi: 10.1161/CIRCRESAHA.120.315890. Epub 2021 Jan 21.

DOI:10.1161/CIRCRESAHA.120.315890
PMID:33476202
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7839236/
Abstract

Atherosclerotic cardiovascular disease (ASCVD) proceeds through a series of stages: initiation, progression (or regression), and complications. By integrating known biology regarding molecular signatures of each stage with recent advances in high-dimensional molecular data acquisition platforms (to assay the genome, epigenome, transcriptome, proteome, metabolome, and gut microbiome), snapshots of each phase of atherosclerotic cardiovascular disease development can be captured. In this review, we will summarize emerging approaches for assessment of atherosclerotic cardiovascular disease risk in humans using peripheral blood molecular signatures and molecular imaging approaches. We will then discuss the potential (and challenges) for these snapshots to be integrated into a personalized movie providing dynamic readouts of an individual's atherosclerotic cardiovascular disease risk status throughout the life course.

摘要

动脉粥样硬化性心血管疾病(ASCVD)经历了一系列阶段:起始、进展(或消退)和并发症。通过整合每个阶段的分子特征的已知生物学知识,以及最近在高维分子数据获取平台方面的进展(检测基因组、表观基因组、转录组、蛋白质组、代谢组和肠道微生物组),可以捕获动脉粥样硬化性心血管疾病发展的每个阶段的快照。在这篇综述中,我们将总结使用外周血分子特征和分子成像方法评估人类动脉粥样硬化性心血管疾病风险的新方法。然后,我们将讨论这些快照被整合到个性化电影中的潜力(和挑战),该电影可以提供个体整个生命过程中动脉粥样硬化性心血管疾病风险状况的动态读数。