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新冠病毒病的心血管特征可预测死亡率并确定稳定屏障的治疗方法。

Cardiovascular signatures of COVID-19 predict mortality and identify barrier stabilizing therapies.

作者信息

Gustafson Dakota, Ngai Michelle, Wu Ruilin, Hou Huayun, Schoffel Alice Carvalhal, Erice Clara, Mandla Serena, Billia Filio, Wilson Michael D, Radisic Milica, Fan Eddy, Trahtemberg Uriel, Baker Andrew, McIntosh Chris, Fan Chun-Po S, Dos Santos Claudia C, Kain Kevin C, Hanneman Kate, Thavendiranathan Paaladinesh, Fish Jason E, Howe Kathryn L

机构信息

Toronto General Hospital Research Institute, University Health Network, Toronto, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada.

Toronto General Hospital Research Institute, University Health Network, Toronto, Canada.

出版信息

EBioMedicine. 2022 Apr;78:103982. doi: 10.1016/j.ebiom.2022.103982. Epub 2022 Apr 8.

Abstract

BACKGROUND

Endothelial cell (EC) activation, endotheliitis, vascular permeability, and thrombosis have been observed in patients with severe coronavirus disease 2019 (COVID-19), indicating that the vasculature is affected during the acute stages of SARS-CoV-2 infection. It remains unknown whether circulating vascular markers are sufficient to predict clinical outcomes, are unique to COVID-19, and if vascular permeability can be therapeutically targeted.

METHODS

Prospectively evaluating the prevalence of circulating inflammatory, cardiac, and EC activation markers as well as developing a microRNA atlas in 241 unvaccinated patients with suspected SARS-CoV-2 infection allowed for prognostic value assessment using a Random Forest model machine learning approach. Subsequent ex vivo experiments assessed EC permeability responses to patient plasma and were used to uncover modulated gene regulatory networks from which rational therapeutic design was inferred.

FINDINGS

Multiple inflammatory and EC activation biomarkers were associated with mortality in COVID-19 patients and in severity-matched SARS-CoV-2-negative patients, while dysregulation of specific microRNAs at presentation was specific for poor COVID-19-related outcomes and revealed disease-relevant pathways. Integrating the datasets using a machine learning approach further enhanced clinical risk prediction for in-hospital mortality. Exposure of ECs to COVID-19 patient plasma resulted in severity-specific gene expression responses and EC barrier dysfunction, which was ameliorated using angiopoietin-1 mimetic or recombinant Slit2-N.

INTERPRETATION

Integration of multi-omics data identified microRNA and vascular biomarkers prognostic of in-hospital mortality in COVID-19 patients and revealed that vascular stabilizing therapies should be explored as a treatment for endothelial dysfunction in COVID-19, and other severe diseases where endothelial dysfunction has a central role in pathogenesis.

FUNDING

This work was directly supported by grant funding from the Ted Rogers Center for Heart Research, Toronto, Ontario, Canada and the Peter Munk Cardiac Center, Toronto, Ontario, Canada.

摘要

背景

在重症冠状病毒病2019(COVID-19)患者中观察到内皮细胞(EC)激活、内皮炎症、血管通透性和血栓形成,这表明在严重急性呼吸综合征冠状病毒2(SARS-CoV-2)感染的急性期脉管系统受到影响。目前尚不清楚循环血管标志物是否足以预测临床结局、是否为COVID-19所特有,以及血管通透性是否可作为治疗靶点。

方法

前瞻性评估241名未接种疫苗的疑似SARS-CoV-2感染患者循环炎症、心脏和EC激活标志物的患病率,并使用随机森林模型机器学习方法开发一个微小RNA图谱,以评估其预后价值。随后的体外实验评估了EC对患者血浆的通透性反应,并用于揭示调控的基因调控网络,从中推断合理的治疗设计。

结果

多种炎症和EC激活生物标志物与COVID-19患者及病情匹配的SARS-CoV-2阴性患者的死亡率相关,而特定微小RNA在疾病表现时的失调对不良的COVID-19相关结局具有特异性,并揭示了与疾病相关的途径。使用机器学习方法整合数据集进一步增强了对住院死亡率的临床风险预测。将EC暴露于COVID-19患者血浆会导致特定严重程度的基因表达反应和EC屏障功能障碍,使用血管生成素-1模拟物或重组Slit2-N可改善这种情况。

解读

多组学数据的整合确定了COVID-19患者住院死亡率的微小RNA和血管生物标志物,并表明应探索血管稳定疗法来治疗COVID-19以及其他在内皮功能障碍在发病机制中起核心作用的严重疾病中的内皮功能障碍。

资金

这项工作得到了加拿大安大略省多伦多市泰德·罗杰斯心脏研究中心和加拿大安大略省多伦多市彼得·芒克心脏中心的赠款直接支持。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/711a/9014368/eab815fb058d/gr1.jpg

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