Translating secondary electrospray ionization-high-resolution mass spectrometry to the clinical environment

Volatilome: Smells like microbial spirit

In recent years, the study of volatile compounds has sparked interest due to their implications in signaling and the enormous variety of bioactive properties attributed to them. Despite the absence of analysis methods standardization, there are a multitude of tools and databases that allow the identification and quantification of volatile compounds. These compounds are chemically heterogeneous and their diverse properties are exploited by various fields such as cosmetics, the food industry, agriculture and medicine, some of which will be discussed here. In virtue of volatile compounds being ubiquitous and fast chemical messengers, these molecules mediate a large number of interspecific and intraspecific interactions, which are key at an ecological level to maintaining the balance and correct functioning of ecosystems. This review briefly summarized the role of volatile compounds in inter- and intra-specific relationships as well as industrial applications associated with the use of these compounds that is emerging as a promising field of study.

Real-time breath analysis towards a healthy human breath profile

The direct analysis of molecules contained within human breath has had significant implications for clinical and diagnostic applications in recent decades. However, attempts to compare one study to another or to reproduce previous work are hampered by: variability between sampling methodologies, human phenotypic variability, complex interactions between compounds within breath, and confounding signals from comorbidities. Towards this end, we have endeavored to create an averaged healthy human 'profile' against which follow-on studies might be compared. Through the use of direct secondary electrospray ionization combined with a high-resolution mass spectrometry and in-house bioinformatics pipeline, we seek to curate an average healthy human profile for breath and use this model to distinguish differences inter- and intra-day for human volunteers. Breath samples were significantly different in PERMANOVA analysis and ANOSIM analysis based on Time of Day, Participant ID, Date of Sample, Sex of Participant, and Age of Participant (p< 0.001). Optimal binning analysis identify strong associations between specific features and variables. These include 227 breath features identified as unique identifiers for 28 of the 31 participants. Four signals were identified to be strongly associated with female participants and one with male participants. A total of 37 signals were identified to be strongly associated with the time-of-day samples were taken. Threshold indicator taxa analysis indicated a shift in significant breath features across the age gradient of participants with peak disruption of breath metabolites occurring at around age 32. Forty-eight features were identified after filtering from which a healthy human breath profile for all participants was created.

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.

A combined screening study for evaluating the potential of exhaled acetone, isoprene, and nitric oxide as biomarkers of lung cancer

Background: the early lung cancer (LC) screening strategy significantly reduces LC mortality. According to previous studies, lung cancer can be effectively diagnosed by analyzing the concentration of volatile organic compounds (VOCs) in human exhaled breath and establishing a diagnosis model based on the different VOCs. This method, called breath analysis, has the advantage of being rapid and non-invasive. To develop a non-invasive, portable breath detection instrument based on cavity ring-down spectroscopy (CRDS), we explored the feasibility of establishing a model with acetone, isoprene, and nitric oxide (NO) exhaled through human breath, which can be detected on the CRDS instrument. Methods: a total of 511 participants were recruited from the Cancer Institute and Hospital, Tianjin Medical University as the discovery set and randomly split (2 : 1) into training set and internal validation set with stratification. For external validation, 51 participants were recruited from the General Hospital, Tianjin Medical University. Acetone and isoprene from exhaled breath were detected by proton-transfer-reaction time-of-flight mass spectrometry (PTR-TOF-MS), and NO was measured using CRDS. The model was constructed using the ensemble learning method that set eXtreme gradient boosting and logistic regression as the basis model and logistic regression as the senior model. The model was evaluated based on accuracy, sensitivity, and specificity. Results: the model achieved an accuracy of 78.8%, sensitivity of 81.0%, specificity of 70.0%, and area under the receiver operating curve (ROC, AUC) of 0.8341 (95% CI from 0.8055 to 0.8852) in the internal validation set. Furthermore, it attained an accuracy of 66.7%, sensitivity of 68.2%, specificity of 65.5%, and AUC of 0.6834 (95% CI from 0.5259 to 0.7956) in the external validation set. Conclusion: the model, established with acetone, isoprene, and NO as predictors, possesses the ability to identify LC patients from healthy control (HC) participants. The CRDS instrument, which simultaneously detects acetone, isoprene, and NO, is expected to be a non-invasive, rapid, portable, and accurate device for early screening of LC.

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.

Detection of Mycobacterium tuberculosis complex field infections in cattle using fecal volatile organic compound analysis through gas chromatography-ion mobility spectrometry combined with chemometrics

Bovine tuberculosis is considered a re-emerging disease caused by different species from the Mycobacterium tuberculosis complex (MTC), important not only for the livestock sector but also for public health due to its zoonotic character. Despite the numerous efforts that have been carried out to improve the performance of the current antemortem diagnostic procedures, nowadays, they still pose several drawbacks, such as moderate to low sensitivity, highlighting the necessity to develop alternative and innovative tools to complement control and surveillance frameworks. Volatilome analysis is considered an innovative approach which has been widely employed in animal science, including animal health field and diagnosis, due to the useful and interesting information provided by volatile metabolites. Therefore, this study assesses the potential of gas chromatography coupled to ion mobility spectrometry (GC-IMS) to discriminate cattle naturally infected (field infections) by MTC from non-infected animals. Volatile organic compounds (VOCs) produced from feces were analyzed, employing the subsequent information through chemometrics. After the evaluation of variable importance for the projection of compounds, the final discriminant models achieved a robust performance in cross-validation, as well as high percentages of correct classification (>90%) and optimal data of sensitivity (91.66%) and specificity (99.99%) in external validation. The tentative identification of some VOCs revealed some coincidences with previous studies, although potential new compounds associated with the discrimination of infected and non-infected subjects were also addressed. These results provide strong evidence that a volatilome analysis of feces through GC-IMS coupled to chemometrics could become a valuable methodology to discriminate the infection by MTC in cattle. IMPORTANCE Bovine tuberculosis is endemic in many countries worldwide and poses important concerns for public health because of their zoonotic condition. However, current diagnostic techniques present several hurdles, such as low sensitivity and complexity, among others. In this regard, the development of new approaches to improve the diagnosis and control of this disease is considered crucial. Volatile organic compounds are small molecular mass metabolites which compose volatilome, whose analysis has been widely employed with success in different areas of animal science including animal health. The present study seeks to evaluate the combination of fecal volatilome analysis with chemometrics to detect field infections by bovine tuberculosis (Mycobacterium tuberculosis complex) in cattle. The good robust performance of discriminant models as well as the optimal data of sensitivity and specificity achieved highlight volatilome analysis as an innovative approach with huge potential.

A cross-sectional study: a breathomics based pulmonary tuberculosis detection method

BACKGROUND

Diagnostics for pulmonary tuberculosis (PTB) are usually inaccurate, expensive, or complicated. The breathomics-based method may be an attractive option for fast and noninvasive PTB detection.

METHOD

Exhaled breath samples were collected from 518 PTB patients and 887 controls and tested on the real-time high-pressure photon ionization time-of-flight mass spectrometer. Machine learning algorithms were employed for breathomics analysis and PTB detection mode, whose performance was evaluated in 430 blinded clinical patients.

RESULTS

The breathomics-based PTB detection model achieved an accuracy of 92.6%, a sensitivity of 91.7%, a specificity of 93.0%, and an AUC of 0.975 in the blinded test set (n = 430). Age, sex, and anti-tuberculosis treatment does not significantly impact PTB detection performance. In distinguishing PTB from other pulmonary diseases (n = 182), the VOC modes also achieve good performance with an accuracy of 91.2%, a sensitivity of 91.7%, a specificity of 88.0%, and an AUC of 0.961.

CONCLUSIONS

The simple and noninvasive breathomics-based PTB detection method was demonstrated with high sensitivity and specificity, potentially valuable for clinical PTB screening and diagnosis.

Current Limitations of Staph Infection Diagnostics, and the Role for VOCs in Achieving Culture-Independent Detection

Staphylococci are broadly adaptable and their ability to grow in unique environments has been widely established, but the most common and clinically relevant staphylococcal niche is the skin and mucous membranes of mammals and birds. S. aureus causes severe infections in mammalian tissues and organs, with high morbidities, mortalities, and treatment costs. S. epidermidis is an important human commensal but is also capable of deadly infections. Gold-standard diagnostic methods for staph infections currently rely upon retrieval and characterization of the infectious agent through various culture-based methods. Yet, obtaining a viable bacterial sample for in vitro identification of infection etiology remains a significant barrier in clinical diagnostics. The development of volatile organic compound (VOC) profiles for the detection and identification of pathogens is an area of intensive research, with significant efforts toward establishing breath tests for infections. This review describes the limitations of existing infection diagnostics, reviews the principles and advantages of VOC-based diagnostics, summarizes the analytical tools for VOC discovery and clinical detection, and highlights examples of how VOC biomarkers have been applied to diagnosing human and animal staph infections.

A gas-phase standard delivery system for direct breath analysis

Applications for direct breath analysis by mass spectrometry (MS) are rapidly expanding. One of the more recent mass spectrometry-based approaches is secondary electrospray ionization coupled to high-resolution mass spectrometry (SESI-HRMS). Despite increasing usage, the SESI methodology still lacks standardization procedures for quality control and absolute quantification. In this study, we designed and evaluated a custom-built standard delivery system tailored for direct breath analysis. The system enables the simultaneous introduction of multiple gas-phase standard compounds into ambient MS setups in the lower parts-per-million (ppm) to parts-per-billion (ppb) range. To best mimic exhaled breath, the gas flow can be heated (37 °C-40 °C) and humidified (up to 98% relative humidity). Inter-laboratory comparison of the system included various SESI-HRMS setups, i.e. an Orbitrap and a quadrupole time-of-flight mass spectrometer (QTOF), and using both single- as well as multi-component standards. This revealed highly stable and reproducible performances with between-run variation <19% and within-run variation <20%. Independent calibration runs demonstrated high accuracy (96%-111%) and precision (>95%) for the single-compound standard acetone, while compound-specific performances were obtained for the multi-component standard. Similarly, the sensitivity varied for different compounds within the multi-component standard across all SESI-Orbitrap and -QTOF setups, yielding limits of detections from 3.1 ppb (forp-xylene) to 0.05 ppb (for 1,8-cineol). Routinely applying the standard system throughout several weeks, allowed us to monitor instrument stability and to identify technical outliers in exhaled breath measurements. Such routine deployment of standards would significantly improve data quality and comparability, which is especially important in longitudinal and multi-center studies. Furthermore, performance validation of the system demonstrated its suitability for reliable absolute quantification while it illustrated compound-dependent behavior for SESI.

Validating Discriminative Signatures for Obstructive Sleep Apnea in Exhaled Breath

Rapid and reliable tools for the diagnosis and monitoring of obstructive sleep apnea (OSA) are currently lacking. Prior studies using a chemical analysis of exhaled breath have suggested the existence of an OSA-specific metabolic signature. Here, we validated this diagnostic approach and the proposed marker compounds, as well as their potential to reliably diagnose OSA. In this cross-sectional observational study, exhaled breath was analyzed using secondary electrospray ionization high-resolution mass spectrometry. The study cohort included untreated OSA patients, OSA patients treated with continuous positive airway pressure and healthy subjects. The robustness of previously reported OSA markers was validated based on detectability, significant differences between groups (Mann–Whitney U test) and classification performance. The breath analysis of 118 participants resulted in 42 previously reported markers that could be confirmed in this independent validation cohort. Nine markers were significantly increased in untreated OSA compared to treated OSA, with a subset of them being consistent with a previous validation study. An OSA prediction based on the confirmed OSA signature performed with an AUC of 0.80 (accuracy 77%, sensitivity 73% and specificity 80%). As several breath markers were clearly found to be repeatable and robust in this independent validation study, these results underscore the clinical potential of breath analysis for OSA diagnostics and monitoring.

A feasibility study of COVID-19 detection using breath analysis by high-pressure photon ionization time-of-flight mass spectrometry

BACKGROUND

SARS-CoV-2 has caused a tremendous threat to global health. PCR and antigen testing have played a prominent role in the detection of SARS-CoV-2-infected individuals and disease control. An efficient, reliable detection tool is still urgently needed to halt the global COVID-19 pandemic. Recently, FDA emergency approved VOC as an alternative test for COVID-19 detection.

METHODS AND MATERIALS

In this case-control study, we prospectively and consecutively recruited 95 confirmed COVID-19 patients and 106 healthy controls in the designated hospital for treatment of COVID-19 patients in Shenzhen, China. Exhaled breath samples were collected and stored in customized bags and then detected by HPPI-TOFMS for volatile organic components (VOCs). Machine learning (ML) algorithms were employed for COVID-19 detection model construction. Participants were randomly assigned in a 5:2:3 ratio to the training, validation, and blinded test sets. The sensitivity (SEN), specificity (SPE), and other general metrics were employed for the VOCs based COVID-19 detection model performance evaluation.

RESULTS

The VOCs based COVID-19 detection model achieved good performance, with a SEN of 92.2% (95% CI: 83.8%, 95.6%), a SPE of 86.1% (95% CI: 74.8%, 97.4%) on blinded test set. Five potential VOC ions related to COVID-19 infection were discovered, which are significantly different between COVID-19 infected patients and controls.

CONCLUSIONS

This study evaluated a simple, fast, non-invasive VOCs-based COVID-19 detection method and demonstrated that it has good sensitivity and specificity in distinguishing COVID-19 infected patients from controls. It has great potential for fast and accurate COVID-19 detection.

A Literature Review and Framework Proposal for Halitosis Assessment in Cigarette Smokers and Alternative Nicotine-Delivery Products Users

Halitosis is a health condition which counts cigarette smoking (CS) among its major risk factors. Cigarette smoke can cause an imbalance in the oral bacterial community, leading to several oral diseases and conditions, including intraoral halitosis. Although the best approach to decrease smoking-related health risks is quitting smoking, this is not feasible for many smokers. Switching to potentially reduced-risk products, like electronic vapor products (EVP) or heated tobacco products (HTP), may help improve the conditions associated with CS. To date, there have been few systematic studies on the effects of CS on halitosis and none have assessed the effects of EVP and HTP use. Self-assessment studies have shown large limitations owing to the lack of reliability in the participants' judgment. This has compelled the scientific community to develop a strategy for meaningful assessment of these new products in comparison with cigarettes. Here, we compiled a review of the existing literature on CS and halitosis and propose a 3-layer approach that combines the use of the most advanced breath analysis techniques and multi-omics analysis to define the interactions between oral bacterial species and their role in halitosis both in vitro and in vivo. Such an approach will allow us to compare the effects of different nicotine-delivery products on oral bacteria and quantify their impact on halitosis. Defining the impact of alternative nicotine-delivery products on intraoral halitosis and its associated bacteria will help the scientific community advance a step further toward understanding the safety of these products and their potentiall risks for consumers.

Personalised therapeutic management of epileptic patients guided by pathway-driven breath metabolomics

BACKGROUND

Therapeutic management of epilepsy remains a challenge, since optimal systemic antiseizure medication (ASM) concentrations do not always correlate with improved clinical outcome and minimal side effects. We tested the feasibility of noninvasive real-time breath metabolomics as an extension of traditional therapeutic drug monitoring for patient stratification by simultaneously monitoring drug-related and drug-modulated metabolites.

METHODS

This proof-of-principle observational study involved 93 breath measurements of 54 paediatric patients monitored over a period of 2.5 years, along with an adult's cohort of 37 patients measured in two different hospitals. Exhaled breath metabolome of epileptic patients was measured in real time using secondary electrospray ionisation-high-resolution mass spectrometry (SESI-HRMS).

RESULTS

We show that systemic ASM concentrations could be predicted by the breath test. Total and free valproic acid (VPA, an ASM) is predicted with concordance correlation coefficient (CCC) of 0.63 and 0.66, respectively. We also find (i) high between- and within-subject heterogeneity in VPA metabolism; (ii) several amino acid metabolic pathways are significantly enriched (p < 0.01) in patients suffering from side effects; (iii) tyrosine metabolism is significantly enriched (p < 0.001), with downregulated pathway compounds in non-responders.

CONCLUSIONS

These results show that real-time breath analysis of epileptic patients provides reliable estimations of systemic drug concentrations along with risk estimates for drug response and side effects.

Application of Volatilome Analysis to the Diagnosis of Mycobacteria Infection in Livestock

Volatile organic compounds (VOCs) are small molecular mass metabolites which compose the volatilome, whose analysis has been widely employed in different areas. This innovative approach has emerged in research as a diagnostic alternative to different diseases in human and veterinary medicine, which still present constraints regarding analytical and diagnostic sensitivity. Such is the case of the infection by mycobacteria responsible for tuberculosis and paratuberculosis in livestock. Although eradication and control programs have been partly managed with success in many countries worldwide, the often low sensitivity of the current diagnostic techniques against Mycobacterium bovis (as well as other mycobacteria from Mycobacterium tuberculosis complex) and Mycobacterium avium subsp. paratuberculosis together with other hurdles such as low mycobacteria loads in samples, a tedious process of microbiological culture, inhibition by many variables, or intermittent shedding of the mycobacteria highlight the importance of evaluating new techniques that open different options and complement the diagnostic paradigm. In this sense, volatilome analysis stands as a potential option because it fulfills part of the mycobacterial diagnosis requirements. The aim of the present review is to compile the information related to the diagnosis of tuberculosis and paratuberculosis in livestock through the analysis of VOCs by using different biological matrices. The analytical techniques used for the evaluation of VOCs are discussed focusing on the advantages and drawbacks offered compared with the routine diagnostic tools. In addition, the differences described in the literature among in vivo and in vitro assays, natural and experimental infections, and the use of specific VOCs (targeted analysis) and complete VOC pattern (non-targeted analysis) are highlighted. This review emphasizes how this methodology could be useful in the problematic diagnosis of tuberculosis and paratuberculosis in livestock and poses challenges to be addressed in future research.

Exhaled volatile organic compounds analysis in clinical pediatrics: a systematic review

BACKGROUND

Measured exhaled volatile organic compounds (VOCs) in breath also referred to as exhaled volatilome have been long claimed as a potential source of non-invasive and clinically applicable biomarkers. However, the feasibility of using exhaled volatilome in clinical practice remains to be demonstrated, particularly in pediatrics where the need for improved non-invasive diagnostic and monitoring methods is most urgent. This work presents the first formal evidence-based judgment of the clinical potential of breath volatilome in the pediatric population.

METHODS

A rigorous systematic review across Web of Science, SCOPUS, and PubMed databases following the PRISMA statement guidelines. A narrative synthesis of the evidence was conducted and QUADAS-2 was used to assess the quality of selected studies.

RESULTS

Two independent reviewers deemed 22 out of the 229 records initially found to satisfy inclusion criteria. A summary of breath VOCs found to be relevant for several respiratory, infectious, and metabolic pathologies was conducted. In addition, we assessed their associated metabolism coverage through a functional characterization analysis.

CONCLUSION

Our results indicate that current research remains stagnant in a preclinical exploratory setting. Designing exploratory experiments in compliance with metabolomics practice should drive forward the clinical translation of VOCs breath analysis.

IMPACT

What is the key message of your article? Metabolomics practice could help to achieve the clinical utility of exhaled volatilome analysis. What does it add to the existing literature? This work is the first systematic review focused on disease status discrimination using analysis of exhaled breath in the pediatric population. A summary of the reported exhaled volatile organic compounds is conducted together with a functional characterization analysis. What is the impact? Having noted challenges preventing the clinical translation, we summary metabolomics practices and the experimental designs that are closer to clinical practice to create a framework to guide future trials.

Mass Spectrometry: A Rosetta Stone to Learn How Fungi Interact and Talk

Fungi are a highly diverse group of heterotrophic organisms that play an important role in diverse ecological interactions, many of which are chemically mediated. Fungi have a very versatile metabolism, which allows them to synthesize a large number of still little-known chemical compounds, such as soluble compounds that are secreted into the medium and volatile compounds that are chemical mediators over short and long distances. Mass spectrometry (MS) is currently playing a dominant role in mycological studies, mainly due to its inherent sensitivity and rapid identification capabilities of different metabolites. Furthermore, MS has also been used as a reliable and accurate tool for fungi identification (i.e., biotyping). Here, we introduce the readers about fungal specialized metabolites, their role in ecological interactions and provide an overview on the MS-based techniques used in fungal studies. We particularly present the importance of sampling techniques, strategies to reduce false-positive identification and new MS-based analytical strategies that can be used in mycological studies, further expanding the use of MS in broader applications. Therefore, we foresee a bright future for mass spectrometry-based research in the field of mycology.

Volatile organic compound breath signatures of children with cystic fibrosis by real-time SESI-HRMS

Early pulmonary infection and inflammation result in irreversible lung damage and are major contributors to cystic fibrosis (CF)-related morbidity. An easy to apply and noninvasive assessment for the timely detection of disease-associated complications would be of high value. We aimed to detect volatile organic compound (VOC) breath signatures of children with CF by real-time secondary electrospray ionisation high-resolution mass spectrometry (SESI-HRMS). A total of 101 children, aged 4-18 years (CF=52; healthy controls=49) and comparable for sex, body mass index and lung function were included in this prospective cross-sectional study. Exhaled air was analysed by a SESI-source linked to a high-resolution time-of-flight mass spectrometer. Mass spectra ranging from m/z 50 to 500 were recorded. Out of 3468 m/z features, 171 were significantly different in children with CF (false discovery rate adjusted p-value of 0.05). The predictive ability (CF versus healthy) was assessed by using a support-vector machine classifier and showed an average accuracy (repeated cross-validation) of 72.1% (sensitivity of 77.2% and specificity of 67.7%). This is the first study to assess entire breath profiles of children with SESI-HRMS and to extract sets of VOCs that are associated with CF. We have detected a large set of exhaled molecules that are potentially related to CF, indicating that the molecular breath of children with CF is diverse and informative.

On-Line Analysis of Exhaled Breath Focus Review

On-line analysis of exhaled breath offers insight into a person's metabolism without the need for sample preparation or sample collection. Due to its noninvasive nature and the possibility to sample continuously, the analysis of breath has great clinical potential. The unique features of this technology make it an attractive candidate for applications in medicine, beyond the task of diagnosis. We review the current methodologies for on-line breath analysis, discuss current and future applications, and critically evaluate challenges and pitfalls such as the need for standardization. Special emphasis is given to the use of the technology in diagnosing respiratory diseases, potential niche applications, and the promise of breath analysis for personalized medicine. The analytical methodologies used range from very small and low-cost chemical sensors, which are ideal for continuous monitoring of disease status, to optical spectroscopy and state-of-the-art, high-resolution mass spectrometry. The latter can be utilized for untargeted analysis of exhaled breath, with the capability to identify hitherto unknown molecules. The interpretation of the resulting big data sets is complex and often constrained due to a limited number of participants. Even larger data sets will be needed for assessing reproducibility and for validation of biomarker candidates. In addition, molecular structures and quantification of compounds are generally not easily available from on-line measurements and require complementary measurements, for example, a separation method coupled to mass spectrometry. Furthermore, a lack of standardization still hampers the application of the technique to screen larger cohorts of patients. This review summarizes the present status and continuous improvements of the principal on-line breath analysis methods and evaluates obstacles for their wider application.

Standardization procedures for real-time breath analysis by secondary electrospray ionization high-resolution mass spectrometry

Despite the attractiveness of breath analysis as a non-invasive means to retrieve relevant metabolic information, its introduction into routine clinical practice remains a challenge. Among all the different analytical techniques available to interrogate exhaled breath, secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS) offers a number of advantages (e.g., real-time, yet wide, metabolome coverage) that makes it ideal for untargeted and targeted studies. However, so far, SESI-HRMS has relied mostly on lab-built prototypes, making it difficult to standardize breath sampling and subsequent analysis, hence preventing further developments such as multi-center clinical studies. To address this issue, we present here a number of new developments. In particular, we have characterized a new SESI interface featuring real-time readout of critical exhalation parameters such as CO₂, exhalation flow rate, and exhaled volume. Four healthy subjects provided breath specimens over a period of 1 month to characterize the stability of the SESI-HRMS system. A first assessment of the repeatability of the system using a gas standard revealed a coefficient of variation (CV) of 2.9%. Three classes of aldehydes, namely 4-hydroxy-2-alkenals, 2-alkenals and 4-hydroxy-2,6-alkedienals―hypothesized to be markers of oxidative stress―were chosen as representative metabolites of interest to evaluate the repeatability and reproducibility of this breath analysis analytical platform. Median and interquartile ranges (IQRs) of CVs for CO₂, exhalation flow rate, and exhaled volume were 3.2% (1.5%), 3.1% (1.9%), and 5.0% (4.6%), respectively. Despite the high repeatability observed for these parameters, we observed a systematic decay in the signal during repeated measurements for the shorter fatty aldehydes, which eventually reached a steady state after three/four repeated exhalations. In contrast, longer fatty aldehydes showed a steady behavior, independent of the number of repeated exhalation maneuvers. We hypothesize that this highly molecule-specific and individual-independent behavior may be explained by the fact that shorter aldehydes (with higher estimated blood-to-air partition coefficients; approaching 100) mainly get exchanged in the airways of the respiratory system, whereas the longer aldehydes (with smaller estimated blood-to-air partition coefficients; approaching 10) are thought to exchange mostly in the alveoli. Exclusion of the first three exhalations from the analysis led to a median CV (IQR) of 6.7 % (5.5 %) for the said classes of aldehydes. We found that such intra-subject variability is in general much lower than inter-subject variability (median relative differences between subjects 48.2%), suggesting that the system is suitable to capture such differences. No batch effect due to sampling date was observed, overall suggesting that the intra-subject variability measured for these series of aldehydes was biological rather than technical. High correlations found among the series of aldehydes support this notion. Finally, recommendations for breath sampling and analysis for SESI-HRMS users are provided with the aim of harmonizing procedures and improving future inter-laboratory comparisons.

Real-Time Breath Analysis Reveals Specific Metabolic Signatures of COPD Exacerbations

BACKGROUND

Exacerbations of COPD are defined by acute worsening of respiratory symptoms leading to a change in therapy. Identifying altered metabolic processes in patients at risk for future exacerbations is desirable for treatment optimization, the development of new therapeutic strategies, and perhaps diagnostic value. We aimed to identify affected pathways using the profiles of volatile organic compounds in exhaled breath from patients with COPD with and without frequent exacerbations (≥ 2 exacerbations within the past 12 months).

METHODS

In this matched cohort study, exhaled breath profiles from patients with COPD and frequent exacerbations ("frequent exacerbators") and without frequent exacerbations ("nonfrequent exacerbators") were analyzed during an exacerbation-free interval using real-time secondary electrospray ionization high-resolution mass spectrometry. We analyzed exhaled breath from 26 frequent exacerbators and 26 nonfrequent exacerbators that were matched in terms of age, sex, and smoking history. To obtain new pathophysiological insights, we investigated significantly altered metabolites, which can be assigned to specific pathways. Metabolites were identified by using a Wilcoxon rank-sum test.

RESULTS

Metabolite levels from the ω-oxidation pathway, namely ω-hydroxy, ω-oxo, and dicarboxylic acids, were consistently decreased in frequent exacerbators. Additionally, several new nitro-aromatic metabolites, which were significantly increased in frequent exacerbators, were identified.

CONCLUSIONS

Real-time breath analysis by secondary electrospray high-resolution mass spectrometry allows molecular profiling of exhaled breath, providing insights about ongoing biochemical processes in patients with COPD at risk for exacerbations.

TRIAL REGISTRY

ClinicalTrials.gov; No.: NCT02186639; URL: www.clinicaltrials.gov.

Beyond monoisotopic accurate mass spectrometry: ancillary techniques for identifying unknown features in non-targeted discovery analysis

High-resolution mass spectrometry (HR-MS) is an important tool for performing non-targeted analysis for investigating complex organic mixtures in human or environmental media. This perspective demonstrates HR-MS compound identification strategies using atom counting, isotope ratios, and fragmentation pattern analysis based on ‘exact’ or ‘accurate’ mass, which allows analytical distinction among mass fragments with the same integer mass, but with different atomic constituents of the original molecules. Herein, HR-MS technology is shown to narrow down the identity of unknown compounds for specific examples, and ultimately inform future analyses when these compounds reoccur. Although HR-MS is important for all biological media, this is particularly critical for new methods and instrumentation invoking exhaled breath condensate, particles, and aerosols. In contrast to standard breath gas-phase analyses where 1 mass unit (Da) resolution is generally sufficient, the condensed phase breath media are particularly vulnerable to errors in compound identification because the larger organic non-volatile molecules can form identical integer mass fragments from different atomic constituents which then require high-resolution mass analyses to tell them apart.