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研究发现COVID19患者血清的蛋白质组学和代谢组学特征
作者:小柯机器人 发布时间:2020/5/29 13:19:27

西湖大学Tiannan Guo、Yi Zhu、温州医科大学Haixiao Chen、迪安诊断公司Huafen Liu等研究人员,合作揭示了COVID-19病人血清的蛋白质组学和代谢组学特征。相关论文于2020年5月27日在线发表在《细胞》杂志上。

研究人员对46个COVID-19患者和53个对照个体的血清进行了蛋白质组学和代谢组学分析。然后,研究人员从18名非严重和13名严重患者的队列中,使用蛋白质组学和代谢组学测量结果训练了机器学习模型。使用十名独立患者对模型进行了验证,其中七名患者已正确分类。
 
在第二批19名新的COVID-19患者的测试队列中,采用了靶向蛋白质组学和代谢组学测定方法来进一步验证该分子分类器,从而得出16个正确的结果。与其他组相比,研究人员确定了COVID-19患者血清中的分子变化,即:巨噬细胞功能失调、血小板脱颗粒和补体系统途径以及大量的代谢抑制。
 
这项研究揭示了重症COVID-19患者血清中特征性蛋白质和代谢产物的变化,可用于选择潜在的血液生物标志物来进行严重程度评估。
 
附:英文原文

Title: Proteomic and Metabolomic Characterization of COVID-19 Patient Sera

Author: Bo Shen, Xiao Yi, Yaoting Sun, Xiaojie Bi, Juping Du, Chao Zhang, Sheng Quan, Fangfei Zhang, Rui Sun, Liujia Qian, Weigang Ge, Wei Liu, Shuang Liang, Hao Chen, Ying Zhang, Jun Li, Jiaqin Xu, Zebao He, Baofu Chen, Jing Wang, Haixi Yan, Yufen Zheng, Donglian Wang, Jiansheng Zhu, Ziqing Kong, Zhouyang Kang, Xiao Liang, Xuan Ding, Guan Ruan, Nan Xiang, Xue Cai, Huanhuan Gao, Lu Li, Sainan Li, Qi Xiao, Tian Lu, Yi Zhu, Huafen Liu, Haixiao Chen, Tiannan Guo

Issue&Volume: 2020-05-27

Abstract: Early detection and effective treatment of severe COVID-19 patients remain major challenges. Here, we performed proteomic and metabolomic profiling of sera from 46 COVID-19 and 53 control individuals. We then trained a machine learning model using proteomic and metabolomic measurements from a training cohort of 18 non-severe and 13 severe patients. The model was validated using ten independent patients, seven of which were correctly classified. Targeted proteomics and metabolomics assays were employed to further validate this molecular classifier in a second test cohort of 19 new COVID-19 patients, leading to 16 correct assignments. We identified molecular changes in the sera of COVID-19 patients compared to other groups implicating dysregulation of macrophage, platelet degranulation and complement system pathways, and massive metabolic suppression. This study revealed characteristic protein and metabolite changes in the sera of severe COVID-19 patients, which might be used in selection of potential blood biomarkers for severity evaluation.

DOI: 10.1016/j.cell.2020.05.032

Source: https://www.cell.com/cell/fulltext/S0092-8674(20)30627-9

期刊信息
Cell:《细胞》,创刊于1974年。隶属于细胞出版社,最新IF:36.216
官方网址:https://www.cell.com/