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.

The rapid, accurate and non-invasive diagnosis of respiratory disease represents a challenge to clinicians, and the development of new treatments can be confounded by insufficient knowledge of lung disease phenotypes. Exhaled breath contains a complex mixture of volatile organic compounds (VOCs), some of which could potentially represent biomarkers for lung diseases. We have developed an adaptive sampling methodology for collecting concentrated samples of exhaled air from participants with impaired respiratory function, against which we employed two-stage thermal desorption gas chromatography-differential mobility spectrometry (GC-DMS) analysis, and showed that it was possible to discriminate between participants with and without chronic obstructive pulmonary disease (COPD). A 2.5 dm(3) volume of end tidal breath was collected onto adsorbent traps (Tenax TA/Carbotrap), from participants with severe COPD and healthy volunteers. Samples were thermally desorbed and analysed by GC-DMS, and the chromatograms analysed by univariate and multivariate analyses. Kruskal-Wallis ANOVA indicated several discriminatory (p < 0.01) signals, with good classification performance (receiver operator characteristic area up to 0.82). Partial least squares discriminant analysis using the full DMS chromatograms also gave excellent discrimination between groups (alpha = 19% and beta = 12.4%).

Sampling of volatile organic compounds (VOCs) has shown promise for detection of a range of diseases but results have proved hard to replicate due to a lack of standardization. In this work we introduce the ‘Peppermint Initiative’. The initiative seeks to disseminate a standardized experiment that allows comparison of breath sampling and data analysis methods. Further, it seeks to share a set of benchmark values for the measurement of VOCs in breath. Pilot data are presented to illustrate the standardized approach to the interpretation of results obtained from the Peppermint experiment. This pilot study was conducted to determine the washout profile of peppermint compounds in breath, identify appropriate sampling time points, and formalise the data analysis. Five and ten participants were recruited to undertake a standardized intervention by ingesting a peppermint oil capsule that engenders a predictable and controlled change in the VOC profile in exhaled breath. After collecting a pre-ingestion breath sample, five further samples are taken at 2, 4, 6, 8, and 10 h after ingestion. Samples were analysed using ion mobility spectrometry coupled to multi-capillary column and thermal desorption gas chromatography mass spectrometry. A regression analysis of the washout data was used to determine sampling times for the final peppermint protocol, and the time for the compound measurement to return to baseline levels was selected as a benchmark value. A measure of the quality of the data generated from a given technique is proposed by comparing data fidelity. This study protocol has been used for all subsequent measurements by the Peppermint Consortium (16 partners from seven countries). So far 1200 breath samples from 200 participants using a range of sampling and analytical techniques have been collected. The data from the consortium will be disseminated in subsequent technical notes focussing on results from individual platforms.

This experiment observed the evolution of metabolite plumes from a human trapped in a simulation of a collapsed building. Ten participants took it in turns over five days to lie in a simulation of a collapsed building and eight of them completed the 6 h protocol while their breath, sweat and skin metabolites were passed through a simulation of a collapsed glass-clad reinforced-concrete building. Safety, welfare and environmental parameters were monitored continuously, and active adsorbent sampling for thermal desorption GC-MS, on-line and embedded CO, CO(2) and O(2) monitoring, aspirating ion mobility spectrometry with integrated semiconductor gas sensors, direct injection GC-ion mobility spectrometry, active sampling thermal desorption GC-differential mobility spectrometry and a prototype remote early detection system for survivor location were used to monitor the evolution of the metabolite plumes that were generated. Oxygen levels within the void simulator were allowed to fall no lower than 19.1% (v). Concurrent levels of carbon dioxide built up to an average level of 1.6% (v) in the breathing zone of the participants. Temperature, humidity, carbon dioxide levels and the physiological measurements were consistent with a reproducible methodology that enabled the metabolite plumes to be sampled and characterized from the different parts of the experiment. Welfare and safety data were satisfactory with pulse rates, blood pressures and oxygenation, all within levels consistent with healthy adults. Up to 12 in-test welfare assessments per participant and a six-week follow-up Stanford Acute Stress Response Questionnaire indicated that the researchers and participants did not experience any adverse effects from their involvement in the study. Preliminary observations confirmed that CO(2), NH(3) and acetone were effective markers for trapped humans, although interactions with water absorbed in building debris needed further study. An unexpected observation from the NH(3) channel was the suppression of NH(3) during those periods when the participants slept, and this will be the subject of further study, as will be the detailed analysis of the casualty detection data obtained from the seven instruments used.

A complex profile of volatile organic compounds ("VOC"s) emanates from human skin, which is altered by changes in the body's metabolic or hormonal state, the external environment, and the bacterial species colonizing the skin surface. The aim of this study was to compare VOC profiles sampled from chronic leg wounds with those from asymptomatic skin. Five participants with chronic arterial leg ulcers were selected. VOC samples were obtained using polydimethylsilicone membranes ("skin-patch method") and analyzed by gas chromatography-ion trap mass spectrometry. Resultant data were analyzed using multivariate analysis and mass spectral matches were compared against the National Institute of Standards and Technology database. Principal component analysis showed differences in profiles obtained from healthy skin and boundary areas and between profiles from healthy skin and lesion samples (p<0.05). Partial least squares for discriminant analysis gave an average prediction accuracy of 73.3% (p<0.05). Mass spectral matching (verified against microbial swab results) identified unique VOCs associated with each sample area, wound bacterial colonization, and ingested medications. This study showcases a reproducible, robust, noninvasive methodology that is applicable in a clinical setting and may offer a new, hitherto unexplored, class of biochemical markers underpinning the metabolism of chronic wounds.

A thermally-desorbed polydimethylsilicone (PDMS) membrane approach with analysis by gas chromatography-mass spectrometry has been developed and characterised, to enable the VOC arising in, and on skin, from glandular secretions, exogenous materials, products of perfusion from blood, and microbiological metabolites to be sampled in a single procedure. In-vitro studies using a series of volatile fatty acid standards indicated that the recovery efficiency of the technique increased with decreasing volatility; for example, the recovery of hexanoic acid was 3.3 times greater than that for 2-methylpropanoic acid. The relative standard deviation of the methodology decreased with decreasing volatility; RSD = 19% for 2-methylpropanoic acid and RSD = 7% for hexanoic acid. Sampled-mass vs. response relationships were modelled satisfactorily using linear regression analysis with regression coefficients in the range 0.95 to 0.998. In-vivo reproducibility was assessed though the analysis of the responses of 1-dodecane, 3,7-dimethyloct-1-ene, 2-propenoic acid, 2-ethylhexyl ester, 2-ethylhexan-1-ol, butanoic, 2-ethylhexylester, and junipen (1,4-methanoazulene, decahydro-4,8,8-trimethyl-9-methylene-); six compounds selected at random retention times from a GC-MS chromatographic VOC profile of human skin containing several hundred resolved and partially resolved compounds. Five samples were obtained simultaneously from the forearm of a healthy male participant. The in-vivo sample masses were estimated to be in the range 50 pg to 100 ng per sample with observed RSD falling between 15% and 32%; in line with a Horwitz trend. Increasing the sample time from 5 min to 120 min generally resulted in an enrichment of the VOC recovered, and for many VOC substantial increases in sensitivity (x7) were observed over this time range as the PDMS sampling-patch approached equilibrium with the underlying skin. Nevertheless, more volatile components, 2,4,6-trimethylcarbazole for instance, were observed to be lost from the analysis with increasing sample time, in a manner analogous with breakthrough behaviour in adsorbent traps. Finally, a 10 day storage study at 4 degrees C suggested that micro-biological factors were significant in their effect on sample stability. Significant changes (up to x8) were observed in the masses of compounds recovered post storage. These studies confirmed that polydimethylsilicone membrane sampling patches of human skin provide rich and analytical useful data. It is important to note that care in experimental design is needed to avoid sampling artefacts being introduced through sampling selectivity, and/or, sample instability where samples are stored for longer than 24 h at 4 degrees C or higher.

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The forehead was studied as a possible sampling site for capturing changes in volatile organic compound (VOC) profiles associated with psychological-stress. Skin-VOCs were sampled with a polydimethylsilicone (PDMS)-coupon and the resulting VOCs were recovered and analysed with two-stage thermal desorption gas chromatography-mass spectrometry.15 young adult volunteers (19 yr to 26 yr) participated in two interventions run in a randomised crossover design. One intervention, termed "Neutral", required the participants to listen to peaceful music, the other, termed a "paced audio serial addition task", required the participants to undertake a series of rapid mental arithmetic calculations in a challenging environment that induced a stress response. Skin-VOC samples were taken during each intervention. The resultant data were processed with dynamic background compensation, deconvolved, and registered to a common retention index scale.The importance of freezing skin patch samplers to -80 o C was determined during the method development phase of this study. The cumulative distribution function of the GC-MS data indicates the possibility that PDMS-coupons are selective towards the lower volatility VOC components in skin. The frequency distribution of the GC-MS data was observed to be approximately log-normal, and on the basis of this study, a further twoorders of magnitude reduction in sensitivity may be required before the complete skin-VOC profile may be characterised.Multi-variate analysis involving Pareto-scaling prior to partial least squares discriminant analysis identified four VOCs with the highest probability of contributing to the variance between the two states, and the responses to these VOCs were modelled with principle components analysis (PCA). Two VOCs, benzoic acid and n-decanoic acid were upregulated (14-and 8-fold respectively) and appear to be PASAT sensitive, with areas under (AUC) their receiver operator characteristic (ROC) curves of 0.813 and 0.852 respectively. A xylene isomer and 3-carene were down regulated 75 % and 97% respectively, and found to be predictive of the neutral intervention (ROC AUC values of 0.898 and 0.929 respectively). VOC profiles in skin appear to change with stress either due to increased elimination, elevated bacterial activity, or perhaps increased oxidative pathways.2