A blood-based host gene expression assay for early detection of respiratory viral infection: an index-cluster prospective cohort study.
A blood-based host gene expression assay for early detection of respiratory viral infection: an index-cluster prospective cohort study.
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一项基于血液的宿主基因表达检测用于呼吸道病毒感染的早期检测：一项指标群前瞻性队列研究
DOI：
10.1016/s1473-3099(20)30486-2
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发表时间：
2021-03
期刊：
影响因子：
--
通讯作者：
Woods CW
中科院分区：
文献类型：
--
作者：
McClain MT;Constantine FJ;Nicholson BP;Nichols M;Burke TW;Henao R;Jones DC;Hudson LL;Jaggers LB;Veldman T;Mazur A;Park LP;Suchindran S;Tsalik EL;Ginsburg GS;Woods CW
早期准确识别病毒感染者对于临床管理和公共卫生干预至关重要。我们的目的是评估转录组学生物标志物在出现典型症状之前识别自然获得性呼吸道病毒感染的能力。在这项指数聚类研究中，我们前瞻性地招募了一组杜克大学（达勒姆，北卡罗来纳州，美国）的本科生（年龄18-25岁），为期5个学年。为了确定指标病例，我们监测了整个学年的学生，使用每日基于网络的调查，对呼吸道感染的八种症状的存在和严重程度进行了监测，症状评分为0-4。指数病例定义为报告每日累积症状评分增加6分的个体。研究工作人员对疑似指示病例进行访视，以确认是否存在报告的疾病症状并采集生物标本样本。然后，我们确定了索引病例的密切接触者（即与索引病例、亲密朋友和伴侣生活在一起的个人）的集群，这些人被认为在观察期间发生症状性呼吸道感染的风险增加。我们对每名密切接触者的症状和病毒脱落进行了5天的监测，并使用基于血液的36基因RT-PCR检测方法在每天的每个时间点测量了转录组学反应。2009年9月1日至2015年4月10日，我们招募了1465名参与者。在264例有呼吸道感染症状的指数病例中，150例（57%）经RT-PCR证实为病毒性病因。在他们的555名密切接触者中，106名（19%）在观察窗口期内出现了经证实的病毒原因引起的有症状的呼吸道感染，其中60名（57%）与其相关的指示病例携带相同的病毒。共检测到9种病毒。转录组学检测准确地预测了最严重症状时的病毒感染（受试者工作特征曲线下的平均面积[AUROC] 0·94 [95% CI 0·92-0·96]），以及第1天（0·87 [95% CI 0·84-0·90]），2天（0·85 [0·82-0·88]）和3天（0.74 [0.71 - 0.77]）在发病高峰期前，当症状最小或不存在时，35例患者中有22例（62%），36例患者中有25例（69%），29例中有24例（82%）未检出病毒脱落。转录生物标志物可以准确地预测和诊断不同病毒原因和疾病阶段的感染，因此可能有助于指导地方性和大流行性传染病背景下的早期有效治疗，检疫决策以及其他临床和公共卫生干预措施。美国国防部高级研究计划局。
Early and accurate identification of individuals with viral infections is crucial for clinical management and public health interventions. We aimed to assess the ability of transcriptomic biomarkers to identify naturally acquired respiratory viral infection before typical symptoms are present. In this index-cluster study, we prospectively recruited a cohort of undergraduate students (aged 18–25 years) at Duke University (Durham, NC, USA) over a period of 5 academic years. To identify index cases, we monitored students for the entire academic year, for the presence and severity of eight symptoms of respiratory tract infection using a daily web-based survey, with symptoms rated on a scale of 0–4. Index cases were defined as individuals who reported a 6-point increase in cumulative daily symptom score. Suspected index cases were visited by study staff to confirm the presence of reported symptoms of illness and to collect biospecimen samples. We then identified clusters of close contacts of index cases (ie, individuals who lived in close proximity to index cases, close friends, and partners) who were presumed to be at increased risk of developing symptomatic respiratory tract infection while under observation. We monitored each close contact for 5 days for symptoms and viral shedding and measured transcriptomic responses at each timepoint each day using a blood-based 36-gene RT-PCR assay. Between Sept 1, 2009, and April 10, 2015, we enrolled 1465 participants. Of 264 index cases with respiratory tract infection symptoms, 150 (57%) had a viral cause confirmed by RT-PCR. Of their 555 close contacts, 106 (19%) developed symptomatic respiratory tract infection with a proven viral cause during the observation window, of whom 60 (57%) had the same virus as their associated index case. Nine viruses were detected in total. The transcriptomic assay accurately predicted viral infection at the time of maximum symptom severity (mean area under the receiver operating characteristic curve [AUROC] 0·94 [95% CI 0·92–0·96]), as well as at 1 day (0·87 [95% CI 0·84–0·90]), 2 days (0·85 [0·82–0·88]), and 3 days (0·74 [0·71–0·77]) before peak illness, when symptoms were minimal or absent and 22 (62%) of 35 individuals, 25 (69%) of 36 individuals, and 24 (82%) of 29 individuals, respectively, had no detectable viral shedding. Transcriptional biomarkers accurately predict and diagnose infection across diverse viral causes and stages of disease and thus might prove useful for guiding the administration of early effective therapy, quarantine decisions, and other clinical and public health interventions in the setting of endemic and pandemic infectious diseases. US Defense Advanced Research Projects Agency.
影响因子：
5.2
作者：
Shurtleff AC;Whitehouse CA;Ward MD;Cazares LH;Bavari S
通讯作者：
Bavari S