Detection and quantification of exhaled volatile organic compounds in mechanically ventilated patients - comparison of two sampling methods

Fulfilling the Promise of Breathomics: Considerations for the Discovery and Validation of Exhaled Volatile Biomarkers

The exhaled breath represents an ideal matrix for noninvasive biomarker discovery, and exhaled metabolomics have the potential to be clinically useful in the era of precision medicine. In this concise translational review, we specifically address volatile organic compounds in the breath, with a view toward fulfilling the promise of these as actionable biomarkers, in particular, for lung diseases. We review the literature paying attention to seminal work linked to key milestones in breath research; discuss potential applications for breath biomarkers across disease areas and healthcare systems, including the perspectives of industry; and outline critical aspects of study design that will need to be considered for any pivotal research going forward if breath analysis is to provide robust validated biomarkers that meet the requirements for future clinical implementation.

Volatile organic compounds and cancer risk assessment in an intensive care unit

Changes caused by air-cleaning devices in the amounts of volatile organic compounds in an intensive care unit were monitored in the study. The cancer risk and hazard index were calculated. The measurements were made for one month at isolated room and two different points and times in the intensive care unit. According to the sampling program, the air-cleaning devices were turned off in weeks 1 and 4 and turned on in weeks 2 and 3. Volatile organic compounds were collected by active sampling. Samples were analyzed by a thermal desorber coupled to a gas chromatography-mass spectrometry instrument with selective ion monitoring. The results showed that the concentrations of benzene, toluene, and o-xylene decreased by about 70% after the air-cleaning devices were installed. The cancer risk assessment for naphthalene was recorded at the highest level of cancer risk (Class A). The hazard index value of naphthalene was recorded at the harmful level when air-cleaning devices were not installed. The concentrations of benzene (p = 0.01), toluene (p = 0.02), ethylbenzene (p = 0.02), styrene (p = 0.01), and m, p-xylene (p = 0.04) before the air-cleaning devices were installed were significantly different from those recorded when the air-cleaning devices were turned on.

Breath metabolomics for diagnosis of acute respiratory distress syndrome

BACKGROUND

Acute respiratory distress syndrome (ARDS) poses challenges in early identification. Exhaled breath contains metabolites reflective of pulmonary inflammation.

AIM

To evaluate the diagnostic accuracy of breath metabolites for ARDS in invasively ventilated intensive care unit (ICU) patients.

METHODS

This two-center observational study included critically ill patients receiving invasive ventilation. Gas chromatography and mass spectrometry (GC-MS) was used to quantify the exhaled metabolites. The Berlin definition of ARDS was assessed by three experts to categorize all patients into "certain ARDS", "certain no ARDS" and "uncertain ARDS" groups. The patients with "certain" labels from one hospital formed the derivation cohort used to train a classifier built based on the five most significant breath metabolites. The diagnostic accuracy of the classifier was assessed in all patients from the second hospital and combined with the lung injury prediction score (LIPS).

RESULTS

A total of 499 patients were included in this study. Three hundred fifty-seven patients were included in the derivation cohort (60 with certain ARDS; 17%), and 142 patients in the validation cohort (47 with certain ARDS; 33%). The metabolites 1-methylpyrrole, 1,3,5-trifluorobenzene, methoxyacetic acid, 2-methylfuran and 2-methyl-1-propanol were included in the classifier. The classifier had an area under the receiver operating characteristics curve (AUROCC) of 0.71 (CI 0.63-0.78) in the derivation cohort and 0.63 (CI 0.52-0.74) in the validation cohort. Combining the breath test with the LIPS does not significantly enhance the diagnostic performance.

CONCLUSION

An exhaled breath metabolomics-based classifier has moderate diagnostic accuracy for ARDS but was not sufficiently accurate for clinical use, even after combination with a clinical prediction score.

Volatilomes of human infection

The human volatilome comprises a vast mixture of volatile emissions produced by the human body and its microbiomes. Following infection, the human volatilome undergoes significant shifts, and presents a unique medium for non-invasive biomarker discovery. In this review, we examine how the onset of infection impacts the production of volatile metabolites that reflects dysbiosis by pathogenic microbes. We describe key analytical workflows applied across both microbial and clinical volatilomics and emphasize the value in linking microbial studies to clinical investigations to robustly elucidate the metabolic species and pathways leading to the observed volatile signatures. We review the current state of the art across microbial and clinical volatilomics, outlining common objectives and successes of microbial-clinical volatilomic workflows. Finally, we propose key challenges, as well as our perspectives on emerging opportunities for developing clinically useful and targeted workflows that could significantly enhance and expedite current practices in infection diagnosis and monitoring.

Microbial Volatiles as Diagnostic Biomarkers of Bacterial Lung Infection in Mechanically Ventilated Patients

BACKGROUND

Early and accurate recognition of respiratory pathogens is crucial to prevent increased risk of mortality in critically ill patients. Microbial-derived volatile organic compounds (mVOCs) in exhaled breath could be used as noninvasive biomarkers of infection to support clinical diagnosis.

METHODS

In this study, we investigated the diagnostic potential of in vitro-confirmed mVOCs in the exhaled breath of patients under mechanical ventilation from the BreathDx study. Samples were analyzed by thermal desorption-gas chromatography-mass spectrometry.

RESULTS

Pathogens from bronchoalveolar lavage (BAL) cultures were identified in 45 of 89 patients and Staphylococcus aureus was the most commonly identified pathogen (n = 15). Of 19 mVOCs detected in the in vitro culture headspace of 4 common respiratory pathogens (S. aureus, Pseudomonas aeruginosa, Klebsiella pneumoniae, and Escherichia coli), 14 were found in exhaled breath samples. Higher concentrations of 2 mVOCs were found in the exhaled breath of patients infected with S. aureus compared to those without (3-methylbutanal: P < .01, area under the receiver operating characteristic curve [AUROC] = 0.81-0.87; and 3-methylbutanoic acid: P = .01, AUROC = 0.79-0.80). In addition, bacteria identified from BAL cultures that are known to metabolize tryptophan (E. coli, Klebsiella oxytoca, and Haemophilus influenzae) were grouped and found to produce higher concentrations of indole compared to breath samples with culture-negative (P = .034) and other pathogen-positive (P = .049) samples.

CONCLUSIONS

This study demonstrates the capability of using mVOCs to detect the presence of specific pathogen groups with potential to support clinical diagnosis. Although not all mVOCs were found in patient samples within this small pilot study, further targeted and qualitative investigation is warranted using multicenter clinical studies.

Validation of volatile metabolites of pulmonary oxidative injury: a bench to bedside study

Background

Changes in exhaled volatile organic compounds (VOCs) can be used to discriminate between respiratory diseases, and increased concentrations of hydrocarbons are commonly linked to oxidative stress. However, the VOCs identified are inconsistent between studies, and translational studies are lacking.

Methods

In this bench to bedside study, we captured VOCs in the headspace of A549 epithelial cells after exposure to hydrogen peroxide (H₂O₂), to induce oxidative stress, using high-capacity polydimethylsiloxane sorbent fibres. Exposed and unexposed cells were compared using targeted and untargeted analysis. Breath samples of invasively ventilated intensive care unit patients (n=489) were collected on sorbent tubes and associated with the inspiratory oxygen fraction (F _IO2 ) to reflect pulmonary oxidative stress. Headspace samples and breath samples were analysed using gas chromatography and mass spectrometry.

Results

In the cell, headspace octane concentration was decreased after oxidative stress (p=0.0013), while the other VOCs were not affected. 2-ethyl-1-hexanol showed an increased concentration in the headspace of cells undergoing oxidative stress in untargeted analysis (p=0.00014). None of the VOCs that were linked to oxidative stress showed a significant correlation with F _IO2 (R_s range: -0.015 to -0.065) or discriminated between patients with F _IO2 ≥0.6 or below (area under the curve range: 0.48 to 0.55).

Conclusion

Despite a comprehensive translational approach, validation of known and novel volatile biomarkers of oxidative stress was not possible in patients at risk of pulmonary oxidative injury. The inconsistencies observed highlight the difficulties faced in VOC biomarker validation, and that caution is warranted in the interpretation of the pathophysiological origin of discovered exhaled breath biomarkers.

Breath and plasma metabolomics to assess inflammation in acute stroke

Inflammation is strongly implicated in both injury and repair processes occurring after stroke. In this exploratory study we assessed the feasibility of repeated sampling of exhaled volatile organic compounds and performed an untargeted metabolomic analysis of plasma collected at multiple time periods after stroke. Metabolic profiles were compared with the time course of the inflammatory markers C-reactive protein (CRP) and interleukin-6 (IL-6). Serial breath sampling was well-tolerated by all patients and the measurement appears feasible in this group. We found that exhaled decanal tracks CRP and IL-6 levels post-stroke and correlates with several metabolic pathways associated with a post-stroke inflammatory response. This suggests that measurement of breath and blood metabolites could facilitate development of novel therapeutic and diagnostic strategies. Results are discussed in relation to the utility of breath analysis in stroke care, such as in monitoring recovery and complications including stroke associated infection.