Identifying and characterizing VOCs in exhaled breath from SARS-CoV-2 positive individuals

Ace Hatch 1, Jason Kinchen 1, Yichen Chen 1, Amy Craster 1, Monika Szkatulska 1, Julian Wright 1, Shane Swann 1, Billy Boyle 1, Orna Barash 2, Efrat Gavriely 2, Roie Shlomovitz 2, Alejandro Orrico-Sánchez 3

1. Owlstone Medical Ltd., Cambridge, Cambridgeshire, UK,

2. Nanoscent Labs, Misgav, North District, Israel,

3. FISABIO-Public Health, Valencia, Spain

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Identifying SARS-CoV-2 infected individuals early in the course of the disease is essential for minimizing spread of COVID-19, however to date, there is no quick and effective way to test large groups of people. Current tests are based on detection of antigens or antibodies in nasal swabs or blood. A breath-based test has the potential to be faster, more accurate, and less invasive. 

Several studies have established volatile organic compounds (VOC) analyses as a promising avenue for the development of COVID-19 diagnostics. A recent meta-analysis found that VOCs could be used to accurately identify patients infected with SARS-CoV-2 with a cumulative sensitivity of 98.2% specificity of 74.3.  This study attempted to identify specific exhaled VOCs that contributed to signals associated with SARS-CoV-2 infection, using Owlstone Medical’s Breath Biopsy® technology. 

Patients enrolled in the study were derived from confirmed COVID-19 cases and controls in Spain and provided breath samples using the ReCIVA® Breath Sampler. Approximately a third of participants provided further breath samples on days 7 and 14 after the baseline collect. Samples were analyzed using the Breath Biopsy OMNI® process in the Breath Biopsy Laboratory. 

Over 1100 individual molecular features were identified by untargeted analysis of the breath samples and included in the final dataset. VOC levels were generally lower in the COVID(+) subgroups than in control COVID(-) patients. Two candidate biomarkers were identified from 91 candidates that showed significant differences in subjects compared to controls. Eight of the top 20 candidate biomarkers were alkanes, thought to result from metabolism associated with inflammation.  




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