Breath analysis combined with cardiopulmonary exercise testing and echocardiography for monitoring heart failure patients: the AEOLUS protocol.

This paper describes the AEOLUS pilot study which combines breath analysis with cardiopulmonary exercise testing (CPET) and an echocardiographic examination for monitoring heart failure (HF) patients. Ten consecutive patients with a prior clinical diagnosis of HF with reduced left ventricular ejection fraction were prospectively enrolled together with 15 control patients with cardiovascular risk factors, including hypertension, type II diabetes or chronic ischemic heart disease. Breath samples were collected at rest and during CPET coupled with exercise stress echocardiography (CPET-ESE) protocol by means of needle trap micro-extraction and were analyzed through gas-chromatography coupled with mass spectrometry. The protocol also involved using of a selected ion flow tube mass spectrometer for a breath-by-breath isoprene and acetone analysis during exercise. At rest, HF patients showed increased breath levels of acetone and pentane, which are related to altered oxidation of fatty acids and oxidative stress, respectively. A significant positive correlation was observed between acetone and the gold standard biomarker NT-proBNP in plasma (r= 0.646,p< 0.001), both measured at rest. During exercise, some exhaled volatiles (e.g., isoprene) mirrored ventilatory and/or hemodynamic adaptation, whereas others (e.g., sulfide compounds and 3-hydroxy-2-butanone) depended on their origin. At peak effort, acetone levels in HF patients differed significantly from those of the control group, suggesting an altered myocardial and systemic metabolic adaptation to exercise for HF patients. These preliminary data suggest that concomitant acquisition of CPET-ESE and breath analysis is feasible and might provide additional clinical information on the metabolic maladaptation of HF patients to exercise. Such information may refine the identification of patients at higher risk of disease worsening.

Biological studies with comprehensive 2D-GC-HRMS screening: Exploring the human sweat volatilome.

A key issue in GCxGC-HRMS data analysis is how to approach large-sample studies in an efficient and comprehensive way. We have developed a semi-automated data-driven workflow from identification to suspect screening, which allows highly selective monitoring of each identified chemical in a large-sample dataset. The example dataset used to illustrate the potential of the approach consisted of human sweat samples from 40 participants, including field blanks (80 samples). These samples have been collected in a Horizon 2020 project to investigate the capacity of body odour to communicate emotion and influence social behaviour. We used dynamic headspace extraction, which allows comprehensive extraction with high preconcentration capability, and has to date only been used for a few biological applications. We were able to detect a set of 326 compounds from a diverse range of chemical classes (278 identified compounds, 39 class unknowns, and 9 true unknowns). Unlike partitioning-based extraction methods, the developed method detects semi-polar (log P < 2) nitrogen and oxygen-containing compounds. However, it is unable to detect certain acids due to the pH conditions of unmodified sweat samples. We believe that our framework will open up the possibility of efficiently using GCxGC-HRMS for large-sample studies in a wide range of applications such as biological and environmental studies.

Identification of Exhaled Metabolites in Children with Cystic Fibrosis.

The early detection of inflammation and infection is important to prevent irreversible lung damage in cystic fibrosis. Novel and non-invasive monitoring tools would be of high benefit for the quality of life of patients. Our group previously detected over 100 exhaled mass-to-charge (m/z) features, using on-line secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS), which distinguish children with cystic fibrosis from healthy controls. The aim of this study was to annotate as many m/z features as possible with putative chemical structures. Compound identification was performed by applying a rigorous workflow, which included the analysis of on-line MS2 spectra and a literature comparison. A total of 49 discriminatory exhaled compounds were putatively identified. A group of compounds including glycolic acid, glyceric acid and xanthine were elevated in the cystic fibrosis group. A large group of acylcarnitines and aldehydes were found to be decreased in cystic fibrosis. The proposed compound identification workflow was used to identify signatures of volatile organic compounds that discriminate children with cystic fibrosis from healthy controls, which is the first step for future non-invasive and personalized applications.

Differentiation of Cystic Fibrosis-Related Pathogens by Volatile Organic Compound Analysis with Secondary Electrospray Ionization Mass Spectrometry.

Identifying and differentiating bacteria based on their emitted volatile organic compounds (VOCs) opens vast opportunities for rapid diagnostics. Secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS) is an ideal technique for VOC-biomarker discovery because of its speed, sensitivity towards polar molecules and compound characterization possibilities. Here, an in vitro SESI-HRMS workflow to find biomarkers for cystic fibrosis (CF)-related pathogens P. aeruginosa, S. pneumoniae, S. aureus, H. influenzae, E. coli and S. maltophilia is described. From 180 headspace samples, the six pathogens are distinguishable in the first three principal components and predictive analysis with a support vector machine algorithm using leave-one-out cross-validation exhibited perfect accuracy scores for the differentiation between the groups. Additionally, 94 distinctive features were found by recursive feature elimination and further characterized by SESI-MS/MS, which yielded 33 putatively identified biomarkers. In conclusion, the six pathogens can be distinguished in vitro based on their VOC profiles as well as the herein reported putative biomarkers. In the future, these putative biomarkers might be helpful for pathogen detection in vivo based on breath samples from patients with CF.

Monitoring peppermint washout in the breath metabolome by secondary electrospray ionization-high resolution mass spectrometry.

In this study, a secondary electrospray ionization-high resolution mass spectrometer (SESI-HRMS) system was employed to profile the real-time exhaled metabolome of ten subjects who had ingested a peppermint oil capsule. In total, six time points were sampled during the experiment. Using an untargeted way of profiling breath metabolome, 2333m/zunique metabolite features were determined in positive mode, and 1322 in negative mode. To benchmark the performance of the SESI-HRMS setup, several additional checks were done, including determination of the technical variation, the biological variation of one subject within three days, the variation within a time point, and the variation across all samples, taking allm/zfeatures into account. Reproducibility was good, with the median technical variation being ∼ 18% and the median variation within biological replicates being ∼ 34%. Both variations were lower than the variation across individuals. Washout profiles of compounds from the peppermint oil, including menthone, limonene, pulegone, menthol and menthofuran were determined in all subjects. Metabolites of the peppermint oil were also determined in breath, for example, cis/trans-carveol, perillic acid and menthol glucuronide. Butyric acid was found to be the major metabolite that reduce the uptake rate of limonene. Pathways related to limonene metabolism were examined, and meaningful pathways were identified from breath metabolomics data acquired by SESI using an untargeted analysis.

Detection of Volatile Organic Compounds with Secondary Electrospray Ionization and Proton Transfer Reaction High-Resolution Mass Spectrometry: A Feature Comparison.

The analysis of volatiles is of high relevance for a wide range of applications from environmental air sampling and security screening to potential medical applications. High-resolution mass spectrometry methods offer a particularly wide compound coverage, sensitivity, and selectivity. Online approaches allow direct analysis in real time without the need for sample preparation. For the first time, we systematically compared the analysis of volatile organic compounds with secondary electrospray ionization (SESI) and proton transfer reaction (PTR) high-resolution mass spectrometry. The selected instruments had comparable mass resolving powers with m/Δm ≥ 15000, which is particularly suitable for nontargeted analysis, for example, of exhaled breath. Exhalations from 14 healthy adults were analyzed simultaneously on both instruments. In addition, 97 reference standards from nine chemical classes were analyzed with a liquid evaporation system. Surprisingly, in breath, we found more complementary than overlapping features. A clear mass dependence was observed for each method with the highest number of detected m/z features for SESI in the high mass region (m/z = 150-250) and for PTR in the low mass region (m/z = 50-150). SESI yielded a significantly higher numbers of peaks (828) compared to PTR (491) among a total of 1304 unique breath m/z features. The number of signals observed by both methods was lower than expected (133 features) with 797 unique SESI features and 374 unique PTR features. Hypotheses to explain the observed mass-dependent differences are proposed.

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.

Molecular breath analysis supports altered amino acid metabolism in idiopathic pulmonary fibrosis.

BACKGROUND AND OBJECTIVE: Diagnosis of idiopathic pulmonary fibrosis (IPF) is complex and its pathogenesis is poorly understood. Recent findings indicate elevated levels of proline and other amino acids in lung tissue of IPF patients which may also be of diagnostic value. Following these findings, we hypothesized that such altered metabolic profiles would be mirrored in exhaled breath and could therefore be captured non-invasively in real time. METHODS: We aimed to validate these results using real-time exhaled breath analysis by secondary electrospray ionization-mass spectrometry, which can provide a non-invasive, painless and fast insight into the metabolism. Breath analysis was performed in a matched 1:1 case-control study involving 21 patients with IPF and 21 control subjects. RESULTS: We found significantly (P < 0.05) elevated levels of proline, 4-hydroxyproline, alanine, valine, leucine/isoleucine and allysine in breath of IPF patients, whereas pyroglutamic acid and phenylalanine did not show significant differences. This coincides with the amino acid's abundance in pulmonary tissue indicating that our observations reflect progressing fibrosis. In addition, amino acid levels correlated across subjects, further supporting a common underlying pathway. We were able to obtain a cross-validated area under the curve of 0.86, suggesting that these increased amino acid levels in exhaled breath have the potential to be used as biomarkers for IPF. CONCLUSION: We could validate previous findings of elevated lung tissue amino acid levels in IPF and show that online breath analysis might be a practical tool for a rapid screening for IPF.

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.

Metabolic changes during periodontitis therapy assessed by real-time ambient mass spectrometry.

It has been shown that bacteria in periodontally diseased patients can be recognized by the detection of volatile metabolites in the headspace of saliva by real-time ambient mass spectrometry. The aim of this study was to use this detection method to analyze the oral metabolome in diseased periodontitis patients before and after therapy to monitor disease evolution and healing events. Twelve patients with advanced chronic periodontal disease and 12 periodontally healthy controls served as test and control groups, respectively. Clinical data, subgingival plaque samples and saliva samples were collected at baseline (BL) and 3 months after treatment. The test group received non-surgical scaling and root planing using systemic antibiotics and the control group received one session of supragingival cleaning. Saliva samples from all subjects were analyzed with ambient mass spectrometry. Significant metabolic alterations were found in the headspace of saliva of periodontitis patients 3 months after the non-surgical periodontal treatment. Furthermore, the diseased group showed metabolic features after the treatment that were similar to the healthy control group. In addition, 29 metabolic features correlated with A. actinomycetemcomitans, 17 features correlated with P. gingivalis and one feature correlated with T. denticola. It was shown that headspace secondary electrospray ionization - mass spectrometry allows the detection of different volatile metabolites in healthy and diseased patients. It can be concluded that this rapid and minimally invasive method could have the potential to routinely diagnose and monitor periodontal diseases in the headspace of saliva samples and, eventually, in exhaled breath.

Real-Time Monitoring of Tricarboxylic Acid Metabolites in Exhaled Breath.

The tricarboxylic acid (TCA) cycle is one of the most important metabolic pathway for cellular respiration in aerobic organisms. It provides and collects intermediates for many other interconnecting pathways and acts as a hub connecting metabolism of carbohydrates, fatty acids, and amino acids. Alteration in intracellular levels of its intermediates has been linked with a wide range of illnesses ranging from cancer to cellular necrosis or liver cirrhosis. Therefore, there exists an intrinsic interest in monitoring such metabolites. Our goal in this study was to evaluate whether, at least the most volatile metabolites of the TCA cycle, could be detected in breath in vivo and in real time. We used secondary electrospray ionization coupled with high-resolution mass spectrometry (SESI-HRMS) to conduct this targeted analysis. We enrolled six healthy individuals who provided full exhalations into the SESI-HRMS system at different times during 3 days. For the first time, we observed exhaled compounds that appertain to the TCA cycle: fumaric, succinic, malic, keto-glutaric, oxaloacetic, and aconitic acids. We found high intraindividual variability and a significant overall difference between morning and afternoon levels for malic acid, oxaloacetic acid, and aconitic acid, supporting previous studies suggesting circadian fluctuations of these metabolites in humans. This study provides first evidence that TCA cycle could conveniently be monitored in breath, opening new opportunities to study in vivo this important metabolic pathway.

Real-time exhaled breath analysis in patients with cystic fibrosis and controls.

We aimed at defining profiles of volatile organic compounds in exhaled breath from patients with cystic fibrosis (CF) using a novel real-time mass spectrometry technique. In this prospective matched case-control study, 30 patients with CF, and 30 healthy control subjects were matched one-to-one according to age, gender, and smoking state. We performed exhaled breath analysis by untargeted secondary electrospray ionization-high resolution mass spectrometry (SESI-HRMS). Patients with CF (mean age 26.0 ± 13.0 years) and controls (mean age 27.9 ± 14.0 years) were analyzed using SESI-HRMS. 49 exhaled breath features were found to be altered (p-value < 0.05/q-value < 0.1) in CF patients, in comparison to healthy controls. The two most discriminating features showed a prediction AUROC of 77.1% (95% CI 62.2%-87.8%) with a specificity of 80.0% and a sensitivity of 63.3%. Levels of oxidative stress metabolites such as fatty acids were found to differ significantly between patients with CF and healthy controls. Furthermore, in patients with CF, 11 features correlated with the mucus concentration of Stenotrophomonas maltophilia bacteria. Exhaled breath analysis with SESI-HRMS allows the identification of CF specific compounds in real-time and may trace bacterial strains in affected patients with CF.

Metabolomic spectral libraries for data-independent SWATH liquid chromatography mass spectrometry acquisition.

High-quality mass spectral libraries have become crucial in mass spectrometry-based metabolomics. Here, we investigate a workflow to generate accurate mass discrete and composite spectral libraries for metabolite identification and for SWATH mass spectrometry data processing. Discrete collision energy (5-100 eV) accurate mass spectra were collected for 532 metabolites from the human metabolome database (HMDB) by flow injection analysis and compiled into composite spectra over a large collision energy range (e.g., 10-70 eV). Full scan response factors were also calculated. Software tools based on accurate mass and predictive fragmentation were specially developed and found to be essential for construction and quality control of the spectral library. First, elemental compositions constrained by the elemental composition of the precursor ion were calculated for all fragments. Secondly, all possible fragments were generated from the compound structure and were filtered based on their elemental compositions. From the discrete spectra, it was possible to analyze the specific fragment form at each collision energy and it was found that a relatively large collision energy range (10-70 eV) gives informative MS/MS spectra for library searches. From the composite spectra, it was possible to characterize specific neutral losses as radical losses using in silico fragmentation. Radical losses (generating radical cations) were found to be more prominent than expected. From 532 metabolites, 489 provided a signal in positive mode [M+H]+ and 483 in negative mode [M-H]-. MS/MS spectra were obtained for 399 compounds in positive mode and for 462 in negative mode; 329 metabolites generated suitable spectra in both modes. Using the spectral library, LC retention time, response factors to analyze data-independent LC-SWATH-MS data allowed the identification of 39 (positive mode) and 72 (negative mode) metabolites in a plasma pool sample (total 92 metabolites) where 81 previously were reported in HMDB to be found in plasma. Graphical abstract Library generation workflow for LC-SWATH MS, using collision energy spread, accurate mass, and fragment annotation.

Mass-Spectrometric Detection of Omega-Oxidation Products of Aliphatic Fatty Acids in Exhaled Breath.

Omega-oxidation is a fatty acid degradation pathway that can occur alternatively to the dominant ß-oxidation. The dysregulation of fatty acid oxidation has been related with a variety of diseases, termed fatty acid oxidation disorders. This work shows evidence for real-time detection in exhaled breath of the complete series of saturated linear ω-hydroxyalkanoic acids, ω-oxoalkanoic acids, and alkanedioic acids with carbon chain lengths of 5-15. We present a comprehensive analytical workflow using online and subsequent offline methods: secondary electrospray ionization mass spectrometry of exhaled breath and UHPLC-HRMS/MS experiments using exhaled breath condensate, respectively. By analyzing online breath measurements of 146 healthy individuals, we were able to obtain strong evidence for the correlation of these metabolite families. This enabled us to monitor the full ω-oxidation pathway in human exhaled breath. We could unambiguously identify these compounds, many of which have never been reported in breath so far. This comprehensive study on breath metabolites reinforces the notion of breath as a valuable source of information, which is underexploited in metabolomics.

Metabolic effects of inhaled salbutamol determined by exhaled breath analysis.

We explore whether real-time breath analysis by high resolution mass spectrometry is suitable to monitor changes at the metabolic level due to inhaling bronchodilator medication. We compared the breath levels of metabolites in a group of patients (n = 50) at baseline and 10 and 30 min after inhalation of 200 µg salbutamol. The same procedure was performed with a group of controls (n = 48) inhaling a placebo spray. A total of 131 mass spectral features were significantly altered as a result of inhaling medication, but not after inhaling placebo. We found that homologous series of chemical classes correlated strongly with each other, strengthening the notion that certain biochemical processes can be monitored. For example, a series of fatty acids was found to be increased after salbutamol intake, suggesting lipolysis stimulation. Peaks corresponding to salbutamol, its main metabolite salbutamol-4-O-sulfate and formoterol were found to be generally increased in patients inhaling the drugs on an as-needed basis, as compared to non-medicated volunteers. Overall, these results suggest such real-time breath analysis is a useful tool for non-invasive therapeutic drug monitoring.

The use of LC predicted retention times to extend metabolites identification with SWATH data acquisition.

The application of predicted LC retention time to support metabolite identification was evaluated for a metabolomics MS/MS database containing 532 compounds representative for the major human metabolite classes. LC retention times could be measured for two C18 type columns using a mobile phase of pH=3.0 for positive ESI mode (n=337, 228) and pH=8.0 for negative ESI mode (n=410, 233). A QSRR modelling was applied with a small set of model compound selected based on the Kennard-Stone algorithm. The models were implemented in the R environment and can be applied to any library. The prediction model was built with two molecular descriptors, LogD2 and the molecular volume. A limited set of model compounds (LC CalMix, n=16) could be validated on two different C18 reversed phase LC columns and with comparable prediction accuracy. The CalMix can be used to compensate for different LC systems. In addition, LC retention prediction was found, in combination with SWATH-MS, to be attractive to eliminate false positive identification as well as for ranking purpose different metabolite isomeric forms.

The Use of Variable Q1 Isolation Windows Improves Selectivity in LC-SWATH-MS Acquisition.

As tryptic peptides and metabolites are not equally distributed along the mass range, the probability of cross fragment ion interference is higher in certain windows when fixed Q1 SWATH windows are applied. We evaluated the benefits of utilizing variable Q1 SWATH windows with regards to selectivity improvement. Variable windows based on equalizing the distribution of either the precursor ion population (PIP) or the total ion current (TIC) within each window were generated by an in-house software, swathTUNER. These two variable Q1 SWATH window strategies outperformed, with respect to quantification and identification, the basic approach using a fixed window width (FIX) for proteomic profiling of human monocyte-derived dendritic cells (MDDCs). Thus, 13.8 and 8.4% additional peptide precursors, which resulted in 13.1 and 10.0% more proteins, were confidently identified by SWATH using the strategy PIP and TIC, respectively, in the MDDC proteomic sample. On the basis of the spectral library purity score, some improvement warranted by variable Q1 windows was also observed, albeit to a lesser extent, in the metabolomic profiling of human urine. We show that the novel concept of "scheduled SWATH" proposed here, which incorporates (i) variable isolation windows and (ii) precursor retention time segmentation further improves both peptide and metabolite identifications.

In silico prediction for the investigation of comedication interferences in quantitative LC-MS detection in the SRM mode.

BACKGROUND: LC-SRM/MS method validation in quantitative bioanalysis requires screening for potential interferences caused by the coelution of comedications or their metabolites. Current approaches are time-consuming, difficult to transfer to other experimental systems and not comprehensive. We propose an in silico strategy based on predicted LC retention time and MS precursor interferences to rank compounds that could potentially interfere with the analyte of interest, followed by a more focused experimental verification. RESULTS: The suggested screening strategy was applied to investigate 129 potential comedications in everolimus patient samples analyzed with a validated LC-SRM/MS assay. A mixture of analytes with the same nominal mass was also investigated to illustrate the interference issues in SRM method development. CONCLUSION: A strategy was developed that allows the rapid screening of comedications, which is scalable to any analyte and transferable to any other LC-MS system.