Zaas Aimee K, Chen Minhua, Varkey Jay, Veldman Timothy, Hero Alfred O, Lucas Joseph, Huang Yongsheng, Turner Ronald, Gilbert Anthony, Lambkin-Williams Robert, Øien N Christine, Nicholson Bradly, Kingsmore Stephen, Carin Lawrence, Woods Christopher W, Ginsburg Geoffrey S
Division of Infectious Diseases and International Health, Department of Medicine, Duke University School of Medicine, Duke University, Durham, NC 27710, USA.
Cell Host Microbe. 2009 Sep 17;6(3):207-17. doi: 10.1016/j.chom.2009.07.006. Epub 2009 Aug 6.
Acute respiratory infections (ARIs) are a common reason for seeking medical attention, and the threat of pandemic influenza will likely add to these numbers. Using human viral challenge studies with live rhinovirus, respiratory syncytial virus, and influenza A, we developed peripheral blood gene expression signatures that distinguish individuals with symptomatic ARIs from uninfected individuals with >95% accuracy. We validated this "acute respiratory viral" signature-encompassing genes with a known role in host defense against viral infections-across each viral challenge. We also validated the signature in an independently acquired data set for influenza A and classified infected individuals from healthy controls with 100% accuracy. In the same data set, we could also distinguish viral from bacterial ARIs (93% accuracy). These results demonstrate that ARIs induce changes in human peripheral blood gene expression that can be used to diagnose a viral etiology of respiratory infection and triage symptomatic individuals.
急性呼吸道感染(ARIs)是寻求医疗护理的常见原因,而大流行性流感的威胁可能会使这一数字增加。通过对人进行鼻病毒、呼吸道合胞病毒和甲型流感病毒的活体病毒挑战研究,我们开发了外周血基因表达特征,可将有症状的ARIs个体与未感染个体区分开来,准确率超过95%。我们在每次病毒挑战中都验证了这种包含在宿主抗病毒感染防御中具有已知作用的基因的“急性呼吸道病毒”特征。我们还在一个独立获取的甲型流感数据集中验证了该特征,并以100%的准确率将感染个体与健康对照区分开来。在同一数据集中,我们还能区分病毒性ARIs和细菌性ARIs(准确率93%)。这些结果表明,ARIs会引起人类外周血基因表达的变化,可用于诊断呼吸道感染的病毒病因并对有症状个体进行分类。