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Background: From a public health perspective, the identification of individuals with mild respiratory symptoms due to SARS-CoV-2 infection is important to contain the spread of the disease. The objective of this study was to identify volatile organic compounds (VOCs) in exhaled breath common to infection with different variants of the SARS-CoV-2 virus to inform the development of a point-of-care breath test to detect infected individuals with mild symptoms., Methods: A prospective, real-world, observational study was conducted on mildly symptomatic out-patients presenting to community test-sites for RT-qPCR SARS-CoV-2 testing when the Alpha, Beta, and Delta variants were driving the COVID-19 pandemic. VOCs in exhaled breath were compared between PCR-positive and negative individuals using TD-GC-ToF-MS. Candidate VOCs were tested in an independent set of samples collected during the Omicron phase of the pandemic., Findings: Fifty breath samples from symptomatic RT-qPCR positive and 58 breath samples from test-negative, but symptomatic participants were compared. Of the 50 RT-qPCR-positive participants, 22 had breath sampling repeated 8-12 weeks later. PCA-X model yielded 12 distinct VOCs that discriminated SARS-CoV-2 active infection compared to recovery/convalescence period, with an area under the receiver operator characteristic curve (AUROC), of 0.862 (0.747-0.977), sensitivity, and specificity of 82% and 86%, respectively. PCA-X model from 50 RT-qPCR positive and 58 negative symptomatic participants, yielded 11 VOCs, with AUROC of 0.72 (0.604-0.803) and sensitivity of 72%, specificity 65.5%. The 11 VOCs were validated in a separate group of SARS-CoV-2 Omicron positive patients' vs healthy controls demonstrating an AUROC of 0.96 (95% CI 0.827-0.993) with sensitivity of 80% specificity of 90%., Interpretation: Exhaled breath analysis is a promising non-invasive, point-of-care method to detect mild COVID-19 infection., Funding: Funding for this study was a competitive grant awarded from the Vancouver Coastal Research Institute as well as funding from the BC Cancer Foundation., Competing Interests: Declaration of interests The authors have no conflict of interest., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: There is an urgent need to rapidly distinguish COVID-19 from other respiratory conditions, including influenza, at first-presentation. Point-of-care tests not requiring laboratory- support will speed diagnosis and protect health-care staff. We studied the feasibility of using breath-analysis to distinguish these conditions with near-patient gas chromatography-ion mobility spectrometry (GC-IMS)., Methods: Independent observational prevalence studies at Edinburgh, UK, and Dortmund, Germany, recruited adult patients with possible COVID-19 at hospital presentation. Participants gave a single breath-sample for VOC analysis by GC-IMS. COVID-19 infection was identified by transcription polymerase chain reaction (RT- qPCR) of oral/nasal swabs together with clinical-review. Following correction for environmental contaminants, potential COVID-19 breath-biomarkers were identified by multi-variate analysis and comparison to GC-IMS databases. A COVID-19 breath-score based on the relative abundance of a panel of volatile organic compounds was proposed and tested against the cohort data., Findings: Ninety-eight patients were recruited, of whom 21/33 (63.6%) and 10/65 (15.4%) had COVID-19 in Edinburgh and Dortmund, respectively. Other diagnoses included asthma, COPD, bacterial pneumonia, and cardiac conditions. Multivariate analysis identified aldehydes (ethanal, octanal), ketones (acetone, butanone), and methanol that discriminated COVID-19 from other conditions. An unidentified-feature with significant predictive power for severity/death was isolated in Edinburgh, while heptanal was identified in Dortmund. Differentiation of patients with definite diagnosis (25 and 65) of COVID-19 from non-COVID-19 was possible with 80% and 81.5% accuracy in Edinburgh and Dortmund respectively (sensitivity/specificity 82.4%/75%; area-under-the-receiver- operator-characteristic [AUROC] 0.87 95% CI 0.67 to 1) and Dortmund (sensitivity / specificity 90%/80%; AUROC 0.91 95% CI 0.87 to 1)., Interpretation: These two studies independently indicate that patients with COVID-19 can be rapidly distinguished from patients with other conditions at first healthcare contact. The identity of the marker compounds is consistent with COVID-19 derangement of breath-biochemistry by ketosis, gastrointestinal effects, and inflammatory processes. Development and validation of this approach may allow rapid diagnosis of COVID-19 in the coming endemic flu seasons., Funding: MR was supported by an NHS Research Scotland Career Researcher Clinician award. DMR was supported by the University of Edinburgh ref COV_29., Competing Interests: DMR and CLPT report a grant from University of Edinburgh. TW reports personal fees from G.A.S. Gesellschaft für analytische Sensorsysteme mbH,  outside the submitted work;  In addition, Dr. Wortelmann has a patent PCT/EP2014/075236 pending.Dr. Wortelmann reports personal fees from G.A.S. Gesellschaft für analytische Sensorsysteme mbH,  outside the submitted work;  In addition, Dr. Wortelmann has a patent PCT/EP2014/075236 pending, (© 2020 The Authors.)

Aim: Breath analyses have potential to detect early signs of disease onset. Ambient ionization allows direct combination of breath gases with MS for fast, on-line analysis. Portable MS systems would facilitate field/clinic-based breath analyses. Results & methodology: Volunteers ingested peppermint oil capsules and exhaled volatile compounds were monitored over 10 h using a compact mass spectrometer. A rise and fall in exhaled menthone was observed, peaking at 60-120 min. Real-time analysis showed a gradual rise in exhaled menthone postingestion. Sensitivity was comparable to established methods, with detection in the parts per trillion range., Conclusion: Breath volatiles were readily analyzed on a portable mass spectrometer through a simple inlet modification. Induced changes in exhaled profiles were detectable with high sensitivity and measurable in real-time.