Discovery and validation of a three-gene signature to distinguish COVID-19 and other viral infections in emergency infectious disease presentations: a case-control and observational cohort study.

Autor:	Li HK; Department of Infectious Disease, Imperial College London, London, UK.; Medical Research Council Centre for Molecular Bacteriology & Infection, Imperial College London, London, UK., Kaforou M; Department of Infectious Disease, Imperial College London, London, UK., Rodriguez-Manzano J; Department of Infectious Disease, Imperial College London, London, UK.; National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infection & Antimicrobial Resistance, Imperial College London, London, UK., Channon-Wells S; Department of Infectious Disease, Imperial College London, London, UK., Moniri A; Department of Electrical & Electronic Engineering, Imperial College London, London, UK., Habgood-Coote D; Department of Infectious Disease, Imperial College London, London, UK., Gupta RK; Institute of Global Health, University College London, London, UK., Mills EA; Department of Infectious Disease, Imperial College London, London, UK., Arancon D; Imperial College Healthcare NHS Trust, London, UK., Lin J; Department of Infectious Disease, Imperial College London, London, UK., Chiu YH; Department of Infectious Disease, Imperial College London, London, UK., Pennisi I; Department of Infectious Disease, Imperial College London, London, UK., Miglietta L; Department of Infectious Disease, Imperial College London, London, UK.; Department of Electrical & Electronic Engineering, Imperial College London, London, UK., Mehta R; Department of Infectious Disease, Imperial College London, London, UK., Obaray N; Department of Infectious Disease, Imperial College London, London, UK., Herberg JA; Department of Infectious Disease, Imperial College London, London, UK., Wright VJ; Department of Infectious Disease, Imperial College London, London, UK., Georgiou P; Department of Electrical & Electronic Engineering, Imperial College London, London, UK.; Centre for Bio-Inspired Technology, Imperial College London, London, UK., Shallcross LJ; Institute of Health Informatics, University College London, London, UK., Mentzer AJ; Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK., Levin M; Department of Infectious Disease, Imperial College London, London, UK., Cooke GS; Department of Infectious Disease, Imperial College London, London, UK., Noursadeghi M; Division of Infection and Immunity, University College London, London, UK., Sriskandan S; Department of Infectious Disease, Imperial College London, London, UK.; Medical Research Council Centre for Molecular Bacteriology & Infection, Imperial College London, London, UK.; National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infection & Antimicrobial Resistance, Imperial College London, London, UK.
Jazyk:	angličtina
Zdroj:	The Lancet. Microbe [Lancet Microbe] 2021 Nov; Vol. 2 (11), pp. e594-e603. Date of Electronic Publication: 2021 Aug 16.
DOI:	10.1016/S2666-5247(21)00145-2
Abstrakt:	Background: 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. Methods: 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. Findings: A three-gene transcript signature, comprising HERC6, IGF1R , and NAGK , 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%. Interpretation: 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. Funding: National Institute for Health Research, Medical Research Council, Wellcome Trust, and EU-FP7. Competing Interests: We declare no competing interests. (© 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.)
Databáze:	MEDLINE
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