Detection of respiratory syncytial virus defective genomes in nasal secretions is associated with distinct clinical outcomes.

Detection of respiratory syncytial virus defective genomes in nasal secretions is associated with distinct clinical outcomes.
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DOI:
10.1038/s41564-021-00882-3
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发表时间:
2021-05
影响因子:
28.3
通讯作者:
--
中科院分区:
生物学1区
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呼吸道合胞病毒(RSV)会导致儿童、免疫功能低下的个人和老年人的呼吸道疾病。然而,影响RSV感染临床结局的病毒因素仍不明确。有缺陷的病毒基因组(DVGs)可以通过竞争病毒蛋白和刺激抗病毒免疫来抑制病毒复制。我们在三个RSV A确认的队列中研究了复制型DVGs的检测与疾病严重程度之间的关系。在住院儿童中,在入院或入院前后的呼吸道样本中检测到DVGs与更严重的疾病、更高的病毒载量和更强的促炎反应密切相关。有趣的是,在实验感染的成年人中,呼吸道分泌物中DVGs的存在与RSV疾病的严重程度不同,这取决于检测到DVGs的时间。感染后早期检测到DVGs与低病毒载量和轻度疾病有关,而感染后较晚检测到DVGs,特别是如果DVGs长期存在,则与高病毒载量和严重疾病相关。综上所述,我们证明DVG蓄积和持续时间的动力学可以预测人类RSV A感染的临床结果,因此可以作为一种预后工具来识别有更严重临床疾病风险的患者。
Respiratory syncytial virus (RSV) causes respiratory illness in children, immunosuppressed individuals and the elderly. However, the viral factors influencing the clinical outcome of RSV infections remain poorly defined. Defective viral genomes (DVGs) can suppress virus replication by competing for viral proteins and by stimulating antiviral immunity. We studied the association between detection of DVGs of the copy-back type and disease severity in three RSV A-confirmed cohorts. In hospitalized children, detection of DVGs in respiratory samples at or around the time of admission associated strongly with more severe disease, higher viral load and a stronger pro-inflammatory response. Interestingly, in experimentally infected adults, the presence of DVGs in respiratory secretions differentially associated with RSV disease severity depending on when DVGs were detected. Detection of DVGs early after infection associated with low viral loads and mild disease, whereas detection of DVGs late after infection, especially if DVGs were present for prolonged periods, associated with high viral loads and severe disease. Taken together, we demonstrate that the kinetics of DVG accumulation and duration could predict clinical outcome of RSV A infection in humans, and thus could be used as a prognostic tool to identify patients at risk of worse clinical disease.
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