Differentiation of COVID-19 from other emergency infectious disease presentations using whole blood transcriptomics then rapid qPCR: a case-control and observational cohort study (preprint)

Background. The overlapping clinical presentations of patients with acute respiratory disease can complicate disease diagnosis. Whilst PCR diagnostic methods to identify SARS-CoV-2 are highly sensitive, they have their shortcomings including false-positive risk and slow turnaround times. Changes in host gene expression can be used to distinguish between disease groups of interest, providing a viable alternative to infectious disease diagnosis. Methods. We interrogated the whole blood gene expression profiles of patients with COVID-19 (n=87), bacterial infections (n=88), viral infections (n=36), and not-infected controls (n=27) to identify a sparse diagnostic signature for distinguishing COVID-19 from other clinically similar infectious and non-infectious conditions. The sparse diagnostic signature underwent validation in a new cohort using reverse transcription quantitative polymerase chain reaction (RT-qPCR) and then underwent further external validation in an independent in silico RNA-seq cohort. Findings. We identified a 10-gene signature (OASL, UBP1, IL1RN, ZNF684, ENTPD7, NFKBIE, CDKN1C, CD44, OTOF, MSR1) that distinguished COVID-19 from other infectious and non-infectious diseases with an AUC of 87.1% (95% CI: 82.6%-91.7%) in the discovery cohort and 88.7% and 93.6% when evaluated in the RT-qPCR validation, and in silico cohorts respectively. Interpretation. Using well-phenotyped samples collected from patients admitted acutely with a spectrum of infectious and non-infectious syndromes, we provide a detailed catalogue of blood gene expression at the time of hospital admission. The findings result in the identification of a 10-gene host diagnostic signature to accurately distinguish COVID-19 from other infection syndromes presenting to hospital. This could be developed into a rapid point-of-care diagnostic test, providing a valuable syndromic diagnostic tool for future early pandemic use.

Pseudotemporal whole blood transcriptional profiling of COVID-19 patients stratified by clinical severity reveals differences in immune responses and possible role of monoamine oxidase B (preprint)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is associated with highly variable clinical outcomes. Studying the temporal dynamics of host whole blood gene expression during SARS-CoV-2 infection can elucidate the biological processes that underlie these diverse clinical phenotypes. We employed a novel pseudotemporal approach using MaSigPro to model and compare the trajectories of whole blood transcriptomic responses in patients with mild, moderate and severe COVID-19 disease. We identified 5,267 genes significantly differentially expressed (SDE) over pseudotime and between severity groups and clustered these genes together based on pseudotemporal trends. Pathway analysis of these gene clusters revealed upregulation of multiple immune, coagulation, platelet and senescence pathways with increasing disease severity and downregulation of T cell, transcriptional and cellular metabolic pathways. The gene clusters exhibited differing pseudotemporal trends. Monoamine oxidase B was the top SDE gene, upregulated in severe>moderate>mild COVID-19 disease. This work provides new insights into the diversity of the host response to SARS-CoV-2 and disease severity and highlights the utility of pseudotemporal approaches in studying evolving immune responses to infectious diseases.

Antiviral metabolite 3'-Deoxy-3',4'-didehydro-cytidine is detectable in serum and identifies acute viral infections including COVID-19 (preprint)

There is a critical need for improved infectious disease diagnostics to enable rapid case identification in a viral pandemic and support targeted antimicrobial prescribing. Here we use high-resolution liquid chromatography coupled with mass spectrometry to compare the admission serum metabolome of patients attending hospital with a range of viral infections, including SARS-CoV-2, to those with bacterial infections, non-infected inflammatory conditions and healthy controls. We demonstrate for the first time that 3'-Deoxy-3',4'-didehydro-cytidine (ddhC), a free base of the only known human antiviral small molecule ddhC-triphosphate (ddhCTP), is detectable in serum. ddhC acts as an accurate biomarker for viral infections, generating an area under the receiver operating characteristic curve of 0.954 (95% confidence interval 0.923-0.986) when comparing viral to non-viral cases. Gene expression of viperin, the enzyme responsible for ddhCTP synthesis, is highly correlated with ddhC, providing a biological mechanism for its increase during viral infection. These findings underline a key future diagnostic role of ddhC in the context of pandemic preparedness and antimicrobial stewardship.

Discovery and Validation of a 3-Gene Transcriptional Signature to Distinguish COVID-19 and Other Viral Infections from Bacterial Sepsis in Adults; A Case-Control then Observational Cohort Study (preprint)

Background: Emergency hospital admissions for infection often lack microbiological diagnostic certainty. Novel approaches to discriminate likelihood of bacterial and viral infections are required to support antimicrobial prescribing decisions and infection control practice. We sought to derive and validate a blood transcriptional signature to differentiate bacterial infections from viral infections including COVID-19.Methods: Blood RNA sequencing was performed on a discovery cohort of adults attending the Emergency Department with confirmed bacteraemia or viral infection. Differentially expressed host genes were subjected to feature selection to derive the most parsimonious discriminating signature. RT-qPCR validation of the signature was then performed in a prospective cohort of patients presenting with undifferentiated fever and a second case-control cohort of patients with bacteraemia or COVID-19.Findings: A 3-gene transcript signature was derived from the discovery cohort of 56 definite bacterial and 27 viral infection cases. In the validation cohort, the signature differentiated bacterial and viral infections with an area under receiver operating characteristic curve (AUC) of 0.976 (95% CI: 0.919-1.000), sensitivity 97.3% and specificity of 100%. The AUC for C-reactive protein and leucocyte count was 0.833 (95% CI: 0.694-0.944) and 0.938 (95% CI: 0.840-0.986) respectively. In the second validation analysis the signature discriminated 34 SARS-CoV-2 positive COVID-19 from 35 bacterial infections with AUC of 0.953 (95% CI: 0.893-0.992), sensitivity 88.6% and specificity of 94.1%.Interpretation: This novel 3-gene signature discriminates viral infections including COVID-19 from bacterial sepsis in adults, outperforming both leucocyte count and CRP, thus potentially providing significant clinical utility in managing acute presentations with infection.Funding Statement: Work in this study was funded by the NIHR Imperial Biomedical Research Centre, the Medical Research Council, the Wellcome Trust and the European Union FP7 (EC-GA 279185) (EUCLIDS).Declaration of Interests: None of the authors have any relevant interest to declare. Ethics Approval Statement: Ethical approval was obtained to take deferred consent from patients from whom an RNA specimen had been collected (or from next of kin or nominated consultee) (REC references 14/SC/0008 and 19/SC/0116).