An inter-correlated cytokine network identified at the center of cytokine storm predicted COVID-19 prognosis.
An inter-correlated cytokine network identified at the center of cytokine storm predicted COVID-19 prognosis.
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在细胞因子风暴中心发现的相互关联的细胞因子网络可预测 COVID-19 的预后
DOI：
10.1016/j.cyto.2020.155365
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发表时间：
2021-03
期刊：
影响因子：
3.8
通讯作者：
Zhu Z
中科院分区：
文献类型：
--
作者：
Liu Y;Chen D;Hou J;Li H;Cao D;Guo M;Ling Y;Gao M;Zhou Y;Wan Y;Zhu Z
死者患者的IL-6，IL-8和IL-5的早期血浆水平显着升高。
IL-6，IL-8和IL-5位于相互关联的细胞因子网络的中心。
IFN-A和IL-2的早期血浆水平与疾病过程的长度正相关。
高炎性反应被认为是急性呼吸窘迫综合征（ARDS）的主要原因，尽管据报道，多种细胞因子与疾病严重程度有关它们的预测值尚未完全阐明，本研究的最大值和早期（在疾病发作后10天内）的浓度为12个质量血浆中的细胞因子与患者的IL-6，IL-8和IL-5的等离子水平始终升高。 2与疾病的长度相关调查结果表明，IL-8，IL-6，IL-5可能在与Covid-19相关的细胞因子风暴中起核心作用，并且早期发现多种血浆细胞因子可能有助于预测这种疾病的预后。
The early and late plasma levels of IL-6, IL-8 and IL-5 elevated significantly in deceased patients. IL-6, IL-8 and IL-5 located at the center of an inter-correlated cytokine network. The early plasma levels of IFN-a and IL-2 positively correlated with the length of disease course. The hyper-inflammatory response is thought to be a major cause of acute respiratory distress syndrome (ARDS) in patients with COVID-19. Although multiple cytokines are reportedly associated with disease severity, the key mediators of SARS-CoV-2 induced cytokine storm and their predictive values have not been fully elucidated. The present study analyzed maximal and early (within 10 days after disease onset) concentrations of 12-plex cytokines in plasma. We found consistently elevated plasma levels of IL-6, IL-8 and IL-5 in patients who were deceased compared with those who had mild/moderate or severe disease. The early plasma concentrations of IFN-a and IL-2 positively correlated with the length of the disease course. Moreover, correlation network analysis showed that IL-6, IL-8, and IL-5 located at the center of an inter-correlated cytokine network. These findings suggested that IL-8, IL-6, IL-5 might play central roles in cytokine storms associated with COVID-19 and that the early detection of multiple plasma cytokines might help to predict the prognosis of this disease.
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影响因子：
168.9
作者：
Huang, Chaolin;Wang, Yeming;Cao, Bin
通讯作者：
Cao, Bin
影响因子：
11.8
作者：
Qin, Chuan;Zhou, Luoqi;Tian, Dai-Shi
通讯作者：
Tian, Dai-Shi
DOI：
10.4049/jimmunol.0900995
发表时间：
2009-10-15
期刊：
Journal of immunology (Baltimore, Md. : 1950)
影响因子：
--
作者：
Crowe CR;Chen K;Pociask DA;Alcorn JF;Krivich C;Enelow RI;Ross TM;Witztum JL;Kolls JK
通讯作者：
Kolls JK
影响因子：
5.4
作者：
Szretter, Kristy J.;Gangappa, Shivaprakash;Katz, Jacqueline M.
通讯作者：
Katz, Jacqueline M.
影响因子：
8.6
作者：
Dessing, Mark C.;van der Sluijs, Koenraad F.;van der Poll, Tom
通讯作者：
van der Poll, Tom