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血小板反应性的多参数表型分析用于人类队列的分层。

Multiparameter phenotyping of platelet reactivity for stratification of human cohorts.

机构信息

Institute for Cardiovascular and Metabolic Research, School of Biological Sciences, University of Reading, Reading, UK.

Department of Haemotology, University of Cambridge, Cambridge, UK; and.

出版信息

Blood Adv. 2021 Oct 26;5(20):4017-4030. doi: 10.1182/bloodadvances.2020003261.

DOI:10.1182/bloodadvances.2020003261
PMID:34474473
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8945618/
Abstract

Accurate and comprehensive assessment of platelet function across cohorts of donors may be key to understanding the risk of thrombotic events associated with cardiovascular disease, and, hence, to help personalize the application of antiplatelet drugs. However, platelet function tests can be difficult to perform and analyze; they also can be unreliable or uninformative and poorly standardized across studies. The Platelet Phenomic Analysis (PPAnalysis) assay and associated open-source software platform were developed in response to these challenges. PPAnalysis utilizes preprepared freeze-dried microtiter plates to provide a detailed characterization of platelet function. The automated analysis of the high-dimensional data enables the identification of subpopulations of donors with distinct platelet function phenotypes. Using this approach, we identified that the sensitivity of a donor's platelets to an agonist and their capacity to generate a functional response are distinct independent metrics of platelet reactivity. Hierarchical clustering of these metrics identified 6 subgroups with distinct platelet phenotypes within healthy cohorts, indicating that platelet reactivity does not fit into the traditional simple categories of "high" and "low" responders. These platelet phenotypes were found to exist in 2 independent cohorts of healthy donors and were stable on recall. PPAnalysis is a powerful tool for stratification of cohorts on the basis of platelet reactivity that will enable investigation of the causes and consequences of differences in platelet function and drive progress toward precision medicine.

摘要

准确全面地评估不同供体群体的血小板功能,可能是理解与心血管疾病相关的血栓形成事件风险的关键,因此有助于实现抗血小板药物的个体化应用。然而,血小板功能检测可能难以进行和分析;在不同的研究中,它们也可能不可靠或没有信息,并且标准化程度较差。血小板表型分析(PPAnalysis)检测及其相关的开源软件平台就是针对这些挑战而开发的。PPAnalysis 利用预先制备的冻干微孔板,对血小板功能进行详细的特征描述。对高维数据的自动分析能够识别出具有不同血小板功能表型的供体亚群。通过这种方法,我们发现供体血小板对激动剂的敏感性及其产生功能反应的能力是血小板反应性的两个独立指标。对这些指标进行层次聚类,在健康供体群体中确定了 6 个具有不同血小板表型的亚群,表明血小板反应性不符合“高”和“低”反应者的传统简单分类。在 2 个独立的健康供体群体中发现了这些血小板表型,并且在随访中是稳定的。PPAnalysis 是一种基于血小板反应性对群体进行分层的强大工具,它将能够研究血小板功能差异的原因和后果,并推动精准医学的发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c0f/8945618/42053ee5773b/advancesADV2020003261f7.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c0f/8945618/42053ee5773b/advancesADV2020003261f7.jpg
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