Volatile compounds released by Nalophan; implications for selected ion flow tube mass spectrometry and other chemical ionisation mass spectrometry analytical methods

Preservation of exhaled breath samples for analysis by off-line SESI-HRMS: proof-of-concept study

Secondary electrospray ionization-high resolution mass spectrometry (SESI-HRMS) is an established technique in the field of breath analysis characterized by its short analysis time, as well as high levels of sensitivity and selectivity. Traditionally, SESI-HRMS has been used for real-time breath analysis, which requires subjects to be at the location of the analytical platform. Therefore, it limits the possibilities for an introduction of this methodology in day-to-day clinical practice. However, recent methodological developments have shown feasibility on the remote sampling of exhaled breath in Nalophan® bags prior to measurement using SESI-HRMS. To further explore the range of applications of this method, we conducted a proof-of-concept study to assess the impact of the storage time of exhaled breath in Nalophan® bags at different temperatures (room temperature and dry ice) on the relative intensities of the compounds. In addition, we performed a detailed study of the storage effect of 27 aldehydes related to oxidative stress. After 2 h of storage, the mean of intensity of allm/zsignals relative to the samples analyzed without prior storage remained above 80% at both room temperature and dry ice. For the 27 aldehydes, the mean relative intensity losses were lower than 20% at 24 h of storage, remaining practically stable since the first hour of storage following sample collection. Furthermore, the mean relative intensity of most aldehydes in samples stored at room temperature was higher than those stored in dry ice, which could be related to water vapor condensation issues. These findings indicate that the exhaled breath samples could be preserved for hours with a low percentage of mean relative intensity loss, thereby allowing more flexibility in the logistics of off-line SESI-HRMS studies.

Prediction of systemic free and total valproic acid by off-line analysis of exhaled breath in epileptic children and adolescents

Therapeutic drug monitoring (TDM) of medications with a narrow therapeutic window is a common clinical practice to minimize toxic effects and maximize clinical outcomes. Routine analyses rely on the quantification of systemic blood concentrations of drugs. Alternative matrices such as exhaled breath are appealing because of their inherent non-invasive nature. This is especially the case for pediatric patients. We have recently showcased the possibility of predicting systemic concentrations of valproic acid (VPA), an anti-seizure medication by real-time breath analysis in two real clinical settings. This approach, however, comes with the limitation of the patients having to physically exhale into the mass spectrometer. This restricts the possibility of sampling from patients not capable or available to exhale into the mass spectrometer located on the hospital premises. In this work, we developed an alternative method to overcome this limitation by collecting the breath samples in customized bags and subsequently analyzing them by secondary electrospray ionization coupled to high-resolution mass spectrometry (SESI-HRMS). A total ofn= 40 patients (mean ± SD, 11.5 ± 3.5 y.o.) diagnosed with epilepsy and taking VPA were included in this study. The patients underwent three measurements: (i) serum concentrations of total and free VPA, (ii) real-time breath analysis and (iii) off-line analysis of exhaled breath collected in bags. The agreement between the real-time and the off-line breath analysis methods was evaluated using Lin's concordance correlation coefficient (CCC). CCC was computed for ten mass spectral predictors of VPA concentrations. Lin's CCC was >0.6 for all VPA-associated features, except for two low-signal intensity isotopic peaks. Finally, free and total serum VPA concentrations were predicted by cross validating the off-line data set. Support vector machine algorithms provided the most accurate predictions with a root mean square error of cross validation of 29.0 ± 7.4 mg l-1and 3.9 ± 1.4 mg l-1for total and free VPA (mean ± SD), respectively. As a secondary analysis, we explored whether exhaled metabolites previously associated with side-effects and response to medication could be rendered by the off-line analysis method. We found that five features associated with side effects showed a CCC > 0.6, whereas none of the drug response-associated peaks reached this cut-off. We conclude that the clinically relevant free fraction of VPA can be predicted by this combination of off-line breath collection with rapid SESI-HRMS analysis. This opens new possibilities for breath based TDM in clinical settings.

Breath Testing in the Surgical Setting: Applications, Challenges, and Future Perspectives

BACKGROUND

The potential for exhaled breath to be a valuable diagnostic tool is often overlooked as it can be difficult to imagine how a barely visible sample of breath could hold such a rich source of information about the state of our health. However, technological advances over the last 50 years have enabled us to detect volatile organic compounds (VOCs) present in exhaled breath, and this provides the key to understanding the wealth of information contained within these readily available samples.

SUMMARY

VOCs are produced as a by-product of metabolism; hence, changes in the underlying physiological processes will be reflected in the exact composition of VOCs in exhaled breath. It has been shown that characteristic changes occur in the breath VOC profile associated with certain diseases including cancer, which may enable the non-invasive detection of cancer at primary care level for patients with vague symptoms. The use of breath testing as a diagnostic tool has many advantages. It is non-invasive and quick, and the test is widely accepted by patients and clinicians. However, breath samples provide a snapshot of the VOCs present in a particular patient at a given point in time, so this can be heavily influenced by external factors such as diet, smoking, and the environment. These must all be accounted for when attempting to draw conclusions about disease status. This review focuses on the current applications for breath testing in the field of surgery, as well as discussing the challenges encountered with developing a breath test in a clinical environment. The future of breath testing in the surgical setting is also discussed, including the translation of breath research into clinical practice.

KEY MESSAGES

Analysis of VOCs in exhaled breath can identify the presence of underlying disease including cancer as well as other infectious or inflammatory conditions. Despite the patient factors, environmental factors, storage, and transport considerations that must be accounted for, breath testing demonstrates ideal characteristics for a triage test, being non-invasive, simple, and universally acceptable to patients and clinicians. Many novel biomarkers and diagnostic tests fail to translate into clinical practice because their potential clinical application does not align with the requirements and unmet needs of the healthcare sector. Non-invasive breath testing, however, has the great potential to revolutionise the early detection of diseases, such as cancer, in the surgical setting for patients with vague symptoms.

Combination of Exhaled Breath Analysis with Parallel Lung Function and FeNO Measurements in Infants

Breath analysis by secondary electrospray ionization-high resolution mass spectrometry (SESI-HRMS) offers the possibility to measure comprehensive metabolic profiles. The technology is currently being deployed in several clinical settings in Switzerland and China. However, patients are required to exhale directly into the device located in a dedicated room. Consequently, clinical implementation in patients incapable of performing necessary exhalation maneuvers (e.g., infants) or immobile (e.g., too weak, elderly, or in intensive care) remains a challenge. The aim of this study was to develop a method to extend such breath analysis capabilities to this subpopulation of patients by collecting breath samples remotely (offline) and promptly (within 10 min) transfer them to SESI-HRMS for chemical analysis. We initially assessed the method in adults by comparing breath mass spectra collected offline with Nalophan bags against spectra of breath samples collected in real time. In total, 13 adults provided 176 pairs of real-time and offline measurements. Lin's concordance correlation coefficient (CCC) was used to estimate the agreement between offline and real-time analyses. Here, 1249 mass spectral features (55% of total detected) exhibited Lin's CCC > 0.6. Subsequently, the method was successfully deployed to analyze breath samples from infants (n = 16), obtaining as a result SESI-HRMS breath profiles. To demonstrate the clinical feasibility of the method, we measured in parallel other clinical variables: (i) lung function, which characterizes the breathing patterns, and (ii) nitric oxide, which is a surrogate marker of airway inflammation. As a showcase, we focused our analysis on the exhaled oxidative stress marker 4-hydroxynonenal and its association with nitric oxide and minute ventilation.

Determination of trace compounds and artifacts in nitrogen background measurements by proton transfer reaction time-of-flight mass spectrometry under dry and humid conditions

A qualitative analysis was applied for the determination of trace compounds at the parts per trillion in volume (ppt_v ) level in the mass spectra of nitrogen of different qualities (5.0 and 6.0) under dry and humid conditions. This qualitative analysis enabled the classification and discovery of hundreds of new ions (e.g., [S_x ]H⁺ species) and artifacts such as parasitic ions and memory effects and their differentiation from real gas impurities. With this analysis, the humidity dependency of all kind of ions in the mass spectrum was determined. Apart from the inorganic artifacts previously discovered, many new organic ions were assigned as instrumental artifacts and new isobaric interferences could be elucidated. From 1140 peaks found in the mass range m/z 0-800, only 660 could be analyzed due to sufficient intensity, from which 463 corresponded to compounds. The number of peaks in nitrogen proton transfer reaction (PTR) spectra was similarly dominated by nonmetallic oxygenated organic compounds (23.5%) and hydrocarbons (24.1%) Regarding only gas impurities, hydrocarbons were the main compound class (50.2%). The highest contribution to the total ion signal for unfiltered nitrogen under dry and humid conditions was from nonmetallic oxygenated compounds. Under dry conditions, nitrogen-containing compounds exhibit the second highest contribution of 89% and 96% for nitrogen 5.0 and 6.0, respectively, whereas under humid conditions, hydrocarbons become the second dominant group with 69% and 86% for nitrogen 5.0 and 6.0, respectively. With the gathered information, a database can be built as a tool for the elucidation of instrumental and intrinsic gas matrix artifacts in PTR mass spectra and, especially in cases, where dilution with inert gases plays a significant role.

Selected ion flow tube mass spectrometry for targeted analysis of volatile organic compounds in human breath

The analysis of volatile organic compounds (VOCs) within breath for noninvasive disease detection and monitoring is an emergent research field that has the potential to reshape current clinical practice. However, adoption of breath testing has been limited by a lack of standardization. This protocol provides a comprehensive workflow for online and offline breath analysis using selected ion flow tube mass spectrometry (SIFT-MS). Following the suggested protocol, 50 human breath samples can be analyzed and interpreted in <3 h. Key advantages of SIFT-MS are exploited, including the acquisition of real-time results and direct compound quantification without need for calibration curves. The protocol includes details of methods developed for targeted analysis of disease-specific VOCs, specifically short-chain fatty acids, aldehydes, phenols, alcohols and alkanes. A procedure to make custom breath collection bags is also described. This standardized protocol for VOC analysis using SIFT-MS is intended to provide a basis for wider application and the use of breath analysis in clinical studies.

Cross Platform Analysis of Volatile Organic Compounds Using Selected Ion Flow Tube and Proton-Transfer-Reaction Mass Spectrometry

Volatile breath metabolites serve as potential disease biomarkers. Online mass spectrometry (MS) presents real-time quantification of breath volatile organic compounds (VOCs). The study aims to assess the relationship between two online analytical mass spectrometry techniques in the quantification of target breath metabolites: selected ion flow tube mass spectrometry (SIFT-MS) and proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS). The two following techniques were employed: (i) direct injection with bag sampling using SIFT-MS and PTR-ToF-MS and (ii) direct injection and thermal desorption (TD) tube comparison using PTR-ToF-MS. The concentration of abundant breath metabolites, acetone and isoprene, demonstrated a strong positive linear correlation between both mass spectrometry techniques (r = 0.97, r = 0.89, respectively; p < 0.001) and between direct injection and TD tube (r = 0.97, r = 0.92, respectively; p < 0.001) breath sampling techniques. This was reflected for the majority of short chain fatty acids and alcohols tested (r > 0.80, p < 0.001). Analyte concentrations were notably higher with the direct injection of a sampling bag compared to the TD method. All metabolites produced a high degree of agreement in the detection range of VOCs between SIFT-MS and PTR-ToF-MS, with the majority of compounds falling within 95% of the limits of agreement with Bland-Altman analysis. The cross platform analysis of exhaled breath demonstrates strong positive correlation coefficients, linear regression, and agreement in target metabolite detection rates between both breath sampling techniques. The study demonstrates the transferability of using data outputs between SIFT-MS and PTR-ToF-MS. It supports the implementation of a TD platform in multi-site studies for breath biomarker research in order to facilitate sample transport between clinics and the laboratory.