Department of Infectious Disease, Imperial College London, London, UK.
Medical Research Council Centre for Molecular Bacteriology & Infection, Imperial College London, London, UK.
Lancet Microbe. 2021 Nov;2(11):e594-e603. doi: 10.1016/S2666-5247(21)00145-2. Epub 2021 Aug 16.
Emergency admissions for infection often lack initial diagnostic certainty. COVID-19 has highlighted a need for novel diagnostic approaches to indicate likelihood of viral infection in a pandemic setting. We aimed to derive and validate a blood transcriptional signature to detect viral infections, including COVID-19, among adults with suspected infection who presented to the emergency department.
Individuals (aged ≥18 years) presenting with suspected infection to an emergency department at a major teaching hospital in the UK were prospectively recruited as part of the Bioresource in Adult Infectious Diseases (BioAID) discovery cohort. Whole-blood RNA sequencing was done on samples from participants with subsequently confirmed viral, bacterial, or no infection diagnoses. Differentially expressed host genes that met additional filtering criteria were subjected to feature selection to derive the most parsimonious discriminating signature. We validated the signature via RT-qPCR in a prospective validation cohort of participants who presented to an emergency department with undifferentiated fever, and a second case-control validation cohort of emergency department participants with PCR-positive COVID-19 or bacterial infection. We assessed signature performance by calculating the area under receiver operating characteristic curves (AUROCs), sensitivities, and specificities.
A three-gene transcript signature, comprising , and , was derived from the discovery cohort of 56 participants with bacterial infections and 27 with viral infections. In the validation cohort of 200 participants, the signature differentiated bacterial from viral infections with an AUROC of 0·976 (95% CI 0·919-1·000), sensitivity of 97·3% (85·8-99·9), and specificity of 100% (63·1-100). The AUROC for C-reactive protein (CRP) was 0·833 (0·694-0·944) and for leukocyte count was 0·938 (0·840-0·986). The signature achieved higher net benefit in decision curve analysis than either CRP or leukocyte count for discriminating viral infections from all other infections. In the second validation analysis, which included SARS-CoV-2-positive participants, the signature discriminated 35 bacterial infections from 34 SARS-CoV-2-positive COVID-19 infections with AUROC of 0·953 (0·893-0·992), sensitivity 88·6%, and specificity of 94·1%.
This novel three-gene signature discriminates viral infections, including COVID-19, from other emergency infection presentations in adults, outperforming both leukocyte count and CRP, thus potentially providing substantial clinical utility in managing acute presentations with infection.
National Institute for Health Research, Medical Research Council, Wellcome Trust, and EU-FP7.
因感染而急诊入院的患者通常缺乏初始诊断的确切依据。COVID-19 凸显了在大流行背景下，需要新的诊断方法来指示病毒感染的可能性。本研究旨在建立和验证一种血液转录谱，以检测包括 COVID-19 在内的病毒感染，该方法针对的是因疑似感染而到急诊就诊的成年人。
本研究前瞻性地招募了英国一家主要教学医院急诊就诊的疑似感染患者（年龄≥18 岁），作为 Bioresource in Adult Infectious Diseases（BioAID）发现队列的一部分。对具有明确病毒、细菌或无感染诊断的参与者的样本进行全血 RNA 测序。对满足其他过滤标准的差异表达宿主基因进行特征选择，以获得最简约的鉴别特征。我们通过对因未明确发热而到急诊就诊的前瞻性验证队列中的参与者进行 RT-qPCR 验证，以及对因 COVID-19 或细菌感染而 PCR 阳性的急诊患者进行二次病例对照验证，对该特征进行了验证。我们通过计算受试者工作特征曲线（AUROC）下面积、敏感性和特异性来评估特征的性能。
从包括 56 例细菌感染和 27 例病毒感染患者的发现队列中提取出一个三基因转录特征，由 、 和 组成。在 200 名验证队列参与者中，该特征区分了细菌和病毒感染，AUROC 为 0.976（95%CI 0.919-1.000），敏感性为 97.3%（85.8-99.9），特异性为 100%（63.1-100）。C 反应蛋白（CRP）的 AUROC 为 0.833（0.694-0.944），白细胞计数的 AUROC 为 0.938（0.840-0.986）。在判别病毒感染与其他所有感染的决策曲线分析中，该特征的净收益高于 CRP 或白细胞计数。在包含 SARS-CoV-2 阳性患者的第二次验证分析中，该特征鉴别了 35 例细菌感染和 34 例 SARS-CoV-2 阳性 COVID-19 感染，AUROC 为 0.953（0.893-0.992），敏感性为 88.6%，特异性为 94.1%。
这个新的三基因特征可鉴别病毒感染，包括 COVID-19，与成年人因其他感染而急诊就诊的情况，其表现优于白细胞计数和 CRP，因此在管理急性感染方面具有很大的临床应用价值。
英国国家卫生研究院、医学研究理事会、惠康信托基金会和欧盟 FP7。
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