Secondary Electrospray Ionization High-Resolution Mass Research Articles

Exhaled breath analysis in patients with potentially curative lung cancer undergoing surgery: a longitudinal study.

Exhaled breath analysis has emerged as a non-invasive and promising method for early detection of lung cancer, offering a novel approach for diagnosis through the identification of specific biomarkers present in a patient's breath. For this longitudinal study, 29 treatment-naive patients with lung cancer were evaluated before and after surgery. Secondary electrospray ionization high-resolution mass spectrometry was used for exhaled breath analysis. Volatile organic compounds with absolute log2 fold change ≥ 1 and q-values ≥ 0.71 were selected as potentially relevant. Exhaled breath analysis resulted in a total of 3482 features. 515 features showed a substantial difference before and after surgery. The small sample size generated a false positive rate of 0.71, therefore, around 154 of these 515 features were expected to be true changes. Biological identification of the features with the highest consistency (m/z -242.18428 and m/z -117.0539) revealed to potentially be 3-Oxotetradecanoic acid and Indole, respectively. Principal component analysis revealed a primary cluster of patients with a recurrent lung cancer, which remained undetected in the initial diagnostic and surgical procedures. The change of exhaled breath patterns after surgery in lung cancer emphasizes the potential for lung cancer screening and detection.

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 all m/z signals 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.

Real-Time Volatile Metabolomics Analysis of Dendritic Cells.

Dendritic cells (DCs) actively sample and present antigen to cells of the adaptive immune system and are thus vital for successful immune control and memory formation. Immune cell metabolism and function are tightly interlinked, and a better understanding of this interaction offers potential to develop immunomodulatory strategies. However, current approaches for assessing the immune cell metabolome are often limited by end-point measurements, may involve laborious sample preparation, and may lack unbiased, temporal resolution of the metabolome. In this study, we present a novel setup coupled to a secondary electrospray ionization-high resolution mass spectrometric (SESI-HRMS) platform allowing headspace analysis of immature and activated DCs in real-time with minimal sample preparation and intervention, with high technical reproducibility and potential for automation. Distinct metabolic signatures of DCs treated with different supernatants (SNs) of bacterial cultures were detected during real-time analyses over 6 h compared to their respective controls (SN only). Furthermore, the technique allowed for the detection of 13C-incorporation into volatile metabolites, opening the possibility for real-time tracing of metabolic pathways in DCs. Moreover, differences in the metabolic profile of naı̈ve and activated DCs were discovered, and pathway-enrichment analysis revealed three significantly altered pathways, including the TCA cycle, α-linolenic acid metabolism, and valine, leucine, and isoleucine degradation.

Exhaled volatile fatty acids, ruminal methane emission, and their diurnal patterns in lactating dairy cows

To date, the commonly used methods to assess rumen fermentation are invasive. Exhaled breath contains hundreds of volatile organic compounds (VOC) that can reflect animal physiological processes. In the present study, for the first time, we aimed to use a noninvasive metabolomics approach based on high-resolution mass spectrometry to identify rumen fermentation parameters in dairy cows. Enteric methane (CH4) production from 7 lactating cows was measured 8 times over 3 consecutive days using the GreenFeed system (C-Lock Technology Inc.). Simultaneously, exhalome samples were collected in Tedlar gas sampling bags and analyzed offline using a secondary electrospray ionization high-resolution mass spectrometry system. In total, 1,298 features were detected, among them targeted exhaled volatile fatty acids (eVFA; i.e., acetate, propionate, butyrate), which were putatively annotated using their exact mass-to-charge ratio. The intensity of eVFA, in particular acetate, increased immediately after feeding and followed a similar pattern to that observed for ruminal CH4 production. The average total eVFA concentration was 35.5 count per second (CPS), and among the individual eVFA, acetate had the greatest concentration, averaging 21.3 CPS, followed by propionate at 11.5 CPS, and butyrate at 2.67 CPS. Further, exhaled acetate was on average the most abundant of the individual eVFA at around 59.3%, followed by 32.5 and 7.9% of the total eVFA for propionate and butyrate, respectively. This corresponds well with the previously reported proportions of these VFA in the rumen. The diurnal patterns of ruminal CH4 emission and individual eVFA were characterized using a linear mixed model with cosine function fit. The model characterized similar diurnal patterns for eVFA and ruminal CH4 and H2 production. Regarding the diurnal patterns of eVFA, the phase (time of peak) of butyrate occurred first, followed by that of acetate and propionate. Importantly, the phase of total eVFA occurred around 1 h before that of ruminal CH4. This corresponds well with existing data on the relationship between rumen VFA production and CH4 formation. Results from the present study revealed a great potential to assess the rumen fermentation of dairy cows using exhaled metabolites as a noninvasive proxy for rumen VFA. Further validation, with comparisons to rumen fluid, and establishment of the proposed method are required.

Online breath analysis with SESI/HRMS for metabolic signatures in children with allergic asthma.

Introduction: There is a need to improve the diagnosis and management of pediatric asthma. Breath analysis aims to address this by non-invasively assessing altered metabolism and disease-associated processes. Our goal was to identify exhaled metabolic signatures that distinguish children with allergic asthma from healthy controls using secondary electrospray ionization high-resolution mass spectrometry (SESI/HRMS) in a cross-sectional observational study. Methods: Breath analysis was performed with SESI/HRMS. Significant differentially expressed mass-to-charge features in breath were extracted using the empirical Bayes moderated t-statistics test. Corresponding molecules were putatively annotated by tandem mass spectrometry database matching and pathway analysis. Results: 48 allergic asthmatics and 56 healthy controls were included in the study. Among 375 significant mass-to-charge features, 134 were putatively identified. Many of these could be grouped to metabolites of common pathways or chemical families. We found several pathways that are well-represented by the significant metabolites, for example, lysine degradation elevated and two arginine pathways downregulated in the asthmatic group. Assessing the ability of breath profiles to classify samples as asthmatic or healthy with supervised machine learning in a 10 times repeated 10-fold cross-validation revealed an area under the receiver operating characteristic curve of 0.83. Discussion: For the first time, a large number of breath-derived metabolites that discriminate children with allergic asthma from healthy controls were identified by online breath analysis. Many are linked to well-described metabolic pathways and chemical families involved in pathophysiological processes of asthma. Furthermore, a subset of these volatile organic compounds showed high potential for clinical diagnostic applications.

Database-assisted, globally optimized targeted secondary electrospray ionization high resolution mass spectrometry (dGOT-SESI-HRMS) and spectral stitching enhanced volatilomics analysis of bacterial metabolites.

Secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS) is an innovative analytical technique for the rapid and non-invasive analysis of volatile organic compounds (VOCs). However, compound annotation and ion suppression in the SESI source has hindered feature detection, stability and reproducibility of SESI-HRMS in untargeted volatilomics. To address this, we have developed and optimized a novel pseudo-targeted approach, database-assisted globally optimized targeted (dGOT)-SESI-HRMS using the microbial-VOC (mVOC) database, and spectral stitching methods to enhance metabolite detection in headspace of anaerobic bacterial cultures. Headspace volatiles from representative bacteria strains were assessed using full scan with data dependent acquisition (DDA), conventional globally optimized targeted (GOT) method, and spectral stitching supported dGOT experiments based on a MS peaks list derived from mVOC. Our results indicate that spectral stitching supported dGOT-SESI-HRMS can proportionally fragment peaks with respect to different analysis windows, with a total of 109 VOCs fragmented from 306 targeted compounds. Of the collected spectra, 88 features were confirmed as culture derived volatiles with respect to media blanks. Annotation was also achieved with a total of 25 unique volatiles referenced to standard databases allowing for biological interpretation. Principal component analysis (PCA) summarizing the headspace volatile demonstrated improved separation of clusters when data was acquired using the dGOT method. Collectively, our dGOT-SESI-HRMS method afforded robust capability of capturing unique VOC profiles from different bacterial strains and culture conditions when compared to conventional GOT and DDA modes, suggesting the newly developed approach can serve as a more reliable analytical method for the sensitive monitoring of gut microbial metabolism.

Effects of a Volatile Organic Compound Filter on Breath Profiles Measured by Secondary Electrospray High-Resolution Mass Spectrometry.

Environmental volatile organic compounds (VOCs) from the ambient air potentially influence on-line breath analysis measurements by secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS). The aim of this study was to investigate how inhaling through a VOC filter affects the detected breath profiles and whether it is feasible to integrate such filters into routine measurements. A total of 24 adult participants performed paired breath analysis measurements with and without the use of an activated carbon filter for inspiration. Concordance correlation coefficients (CCCs) and the Bland−Altman analysis were used to assess the agreement between the two methods. Additionally, the effect on a selection of known metabolites and contaminants was analyzed. Out of all the detected features, 78.3% showed at least a moderate agreement before and after filter usage (CCC > 0.9). The decrease in agreement of the remaining m/z features was mostly associated with reduced signal intensities after filter usage. Although a moderate-to-substantial concordance was found for almost 80% of the m/z features, the filter still had an effect by decreasing signal intensities, not only for contaminants, but also for some of the studied metabolites. Operationally, the use of the filter complicated and slowed down the conductance of measurements, limiting its applicability in clinical studies.

An interoperability framework for multicentric breath metabolomic studies.

Exhaled breath contains valuable information at the molecular level and offers promising potential for precision medicine. However, few breath tests transition to routine clinical practice, partly because of the missing validation in multicenter trials. Therefore, we developed and applied an interoperability framework for standardized multicenter data acquisition and processing for breath analysis with secondary electrospray ionization-high resolution mass spectrometry. We aimed to determine the technical variability and metabolic coverage. Comparison of multicenter data revealed a technical variability of ∼20% and a core signature of the human exhaled metabolome consisting of ∼850 features, corresponding mainly to amino acid, xenobiotic, and carbohydrate metabolic pathways. In addition, we found high inter-subject variability for certain metabolic classes (e.g., amino acids and fatty acids), whereas other regions such as the TCA cycle were relatively stable across subjects. The interoperability framework and overview of metabolic coverage presented here will pave the way for future large-scale multicenter trials.

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.

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.

Rapid detection of Staphylococcus aureus and Streptococcus pneumoniae by real-time analysis of volatile metabolites

SummaryEarly detection of pathogenic bacteria is needed for rapid diagnostics allowing adequate and timely treatment of infections. In this study, we show that secondary electrospray ionization–high resolution mass spectrometry (SESI-HRMS) can be used as a diagnostic tool for rapid detection of bacterial infections as a supportive system for current state-of-the-art diagnostics. Volatile organic compounds (VOCs) produced by growing S. aureus or S. pneumoniae cultures on blood agar plates were detected within minutes and allowed for the distinction of these two bacteria on a species and even strain level within hours. Furthermore, we obtained a fingerprint of clinical patient samples within minutes of measurement and predominantly observed a separation of samples containing live bacteria compared to samples with no bacterial growth. Further development of this technique may reduce the time required for microbiological diagnosis and should help to improve patient’s tailored treatment.

Breath response following a nutritional challenge monitored by secondary electrospray ionization high-resolution mass spectrometry

On-line breath analysis using secondary electrospray ionization coupled to high-resolution mass spectrometry (SESI-HRMS) is a sensitive method for biomarker discovery. The strengths of this technology have already been demonstrated in the clinical environment. For the first time, this study demonstrates the application of SESI-HRMS in the field of nutritional science using a standardized nutritional intervention, consisting of a high-energy shake (950 kcal, 8% protein, 35% sugar and 57% fat). Eleven subjects underwent the intervention on three separate days and their exhaled breath was monitored up to six hours postprandially. In addition, sampling was performed during equivalent fasting conditions for selected subjects. To estimate the impact of inter- and intra-individual variability, analysis of variance simultaneous component analysis was conducted, revealing that the inter-individual variability accounted for 30% of the data variation. To distinguish the effect of the intervention from fasting conditions, partial least squares discriminant analysis was performed. Candidate compound annotation was performed with pathway analysis and collision-induced dissociation (CID) experiments. Pathway analysis highlighted, among others, features associated with the metabolism of linoleate, butanoate and amino sugars. Tentative compounds annotated through CID measurements include fatty acids, amino acids, and amino acid derivatives, some of them likely derived from nutrients by the gut microbiome (e.g. propanoate, indoles), as well as organic acids from the Krebs cycle. Time-series clustering showed an overlap of observed kinetic trends with those reported previously in blood plasma.

In vivo detection of metabolic 2H-incorporation upon ingestion of 2H2O

Abstract Objective: The aim of this work was to explore the feasibility of in vivo and non-invasive monitoring of deuterium/hydrogen (2H/1H) exchange at the metabolic level upon exposure to heavy water (2H2O). Methods: The healthy female mice were randomly assigned to two groups after day 0 when both mice received standard drinking water. The treated mouse was fed with 2H2O (80%, v/v) and the control mouse fed with standard drinking water (H2O) over next 13 days. Real-time mass spectrometric analysis of volatile metabolism emitted through breathing and the skin was performed on days 1, 2, 3, 10, 12, and 13. Animal experiment was approved by the Laboratory Animal Ethics Committee of Jinan University (approval No. 20161117163322) on October 29, 2021. Results: We observed a replacement of 1Hby2H in 52 mass spectral features (60 2H/1 H isotopologue pairs) for the mouse fed with 2H2O, but not for the control mouse. These included pyruvic acid and lactic acid, lysine and methyl-lysine as well as short-chain fatty acids comprising acetic acid, propionic acid, butyric acid and valeric acid. Conclusion: Secondary electrospray ionization-high resolution mass spectrometry allows monitoring in vivo 2H-incorporation of metabolites in a non-invasive and real-time setup and opens new opportunities to use 2H tracing to extend current metabolic studies, especially those with a focus on anaerobic glycolysis, lysine methylation and gut microbiome via monitoring of short-chain fatty acids.

Trends in Direct Breath Analysis by Secondary Electrospray Ionization Mass Spectrometry for Clinical Applications

Exhaled breath can reveal insights about the metabolic state of the human body through the endo- and exogenous compounds it contains. The extent of detectable compounds, however, was revolutionized by the application of mass spectrometry. More specifically, secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS) enables the detection of a broad range of breath-derived compounds simultaneously and with high sensitivity. Together with its rapid and non-invasive nature, direct breath analysis by SESI-HRMS raised particular interest for clinical applications. Over the past years, various clinical trials successfully demonstrated the technology´s capability for biomarker discovery in exhaled breath in adults and more recently in children. Current challenges lie within the potential translation of SESI-HRMS into clinical settings and the requirements therein, such as biomarker identification and validation, which became a focus of more recent studies.

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.

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.

Secondary electrospray ionization-high resolution mass spectrometry (SESI-HRMS) fingerprinting enabled treatment monitoring of pulmonary carcinoma cells in real time

Lung cancer is one of the leading causes of cancer related deaths in the United States. A novel volatile analysis platform is needed to complement current diagnostic techniques and better elucidate chemical signatures of lung cancer and subsequent treatments. A systems biology bottom-up approach using cell culture volatilomics was employed to identify pathological volatile fingerprints of lung cancer in real time. An advanced secondary electrospray ionization (SESI) source, named SuperSESI was used in this study and directly attached to a Thermo Q-Exactive high-resolution mass spectrometer (HRMS). We performed a series of experiments to determine if our optimized SESI-HRMS platform can distinguish between cancer types by sampling their in vitro volatilome profiles. We detected 60 significant volatile organic compound (VOC) features in positive mode that were deemed of cancer cell origin. The cell derived features were used for subsequent analyses to distinguish between our two studied lung cancer types, non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). Partial least squares-discriminant analysis (PLS-DA) model revealed a good separation of the two cancer types, suggesting unique chemical composition of their headspace profiles. A receiver operating characteristic (ROC) curve using 10 prominent features was used to predict disease type, with an area under the curve (AUC) of 0.811. Cultures were also treated with cisplatin to determine the feasibility of classifying drug treatment from expelled gases. A PLS-DA model revealed independent clustering based on their headspace profiles. An ROC curve using the top features driving separation of PLS-DA model suggested good accuracy with an AUC of 1. It is thus possible to benefit from the advantages of this platform to distinguish the unique volatile fingerprints of cancers to uncover potential biomarkers for cancer type differentiation and treatment monitoring.

Quantification of volatile organic compounds by secondary electrospray ionization-high resolution mass spectrometry

Secondary electrospray ionization coupled with high resolution mass spectrometry (SESI-HRMS) is a direct mass spectrometry technique, which can identify trace volatile organic compounds (VOCs) in real time without sample pretreatment and chromatographic separation. SESI-HRMS has been successfully applied in multiple applications, including breath analysis, animals and plants VOCs emissions, analysis of headspace of cell cultures and indoor and outdoor air. The range of areas where the technique can potentially have a substantial impact is very broad. However, one critical aspect that requires further development to consolidate the technique is absolute quantification. Therefore, in this study we aim to develop a quantitative method for eight representative VOCs, including ketones (acetone, 2-butanone and 2-pentanone), alkenes (isoprene and α-terpinene) and aromatics (toluene, styrene and mesitylene). The mass spectrometric platform includes a commercial SESI source hyphenated with a Q-Exactive hybrid quadrupole Orbitrap high resolution mass spectrometer. Within the concentration range of 0–100 ppbv studied, the optimal coefficient of determination for linear regression (R2 = 0.993–0.999) between signal intensity and concentration is obtained in the range of 0–10 ppbv for all eight VOCs. The detection limits range between 3 (2-Pentanone) and 15 (Acetone) pptv. The intra-day (n = 10) and inter-day (n = 30) coefficients of variation (CV) are ≤ 6% and ≤10%, respectively. Finally the method is applied for the fast evaluation (<5 min) of different materials widely used for the collection, storage or pretreatment of gas sample. Better recovery of trace levels of eight VOCs is observed for PTFE gas sampling bag as compared to Nalophan and Tedlar bags; when Nafion tube is used to pretreat the gas sample, recovery of ≤50% are obtained for 2-pentanone, α-terpinene and all three aromatics.

Validation of breath biomarkers for obstructive sleep apnea

Background and objectivesObstructive sleep apnea (OSA) is an underdiagnosed respiratory disease with negative metabolic and cardiovascular effects. The current gold standard for diagnosing OSA is in-hospital polysomnography, a time-consuming and costly procedure, often inconvenient for the patient. Recent studies revealed evidence for the potential of breath analysis for the diagnosis of OSA based on a disease-specific metabolic pattern. However, none of these findings were validated in a larger and broader cohort, an essential step for its application in clinics. MethodsIn the present study, we validated a panel of breath biomarkers in a cohort of patients with possible OSA (N = 149). These markers were previously identified in our group by secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS). ResultsHere, we could confirm significant differences between metabolic patterns in exhaled breath from OSA patients compared to control subjects without OSA as well as the association of breath biomarker levels with disease severity. Our prediction of the diagnosis for the patients from this completely independent validation study using a classification model trained on the data from the previous study resulted in an area under the receiver operating characteristic curve of 0.66, which is comparable to questionnaire-based OSA screenings. ConclusionsThus, our results suggest that breath analysis by SESI-HRMS might be useful to screen for OSA as an objective measure. However, its true predictive power should be tested in combination with OSA screening questionnaires. Clinical trial“Mass Spectral Fingerprinting in Obstructive Sleep Apnoea”, NCT02810158, www.ClinicalTrials.gov.

Minimizing ion competition boosts volatile metabolome coverage by secondary electrospray ionization orbitrap mass spectrometry

Secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS) is an emerging technique for the detection of volatile metabolites. However, sensitivity and reproducibility of SESI-HRMS have limited its applications in untargeted metabolomics profiling. Ion suppression in the SESI source has been considered to be the main cause. Here, we show that besides ion suppression, ion competition in the C-trap of Orbitrap instruments is another important factor that influences sensitivity and reproducibility of SESI-MS. Instead of acquiring the full mass-to-charge ratio (m/z) range, acquisition of consecutive m/z windows to minimize the ion competition effect allows the detection of more features. m/z window ranges are optimized to fill the C-trap either with an equal number of features or an equal cumulative intensity per window. Considering a balance between maximizing scanning speed and minimizing ion competition, splitting the m/z = 50–500 range into 4 windows is selected for measuring human breath and bacterial culture samples on SESI-Orbitrap MS, corresponding to a duty cycle of 2.3 s at a resolution of 140′000. In a small cohort of human subjects, the proposed splitting into 4 windows allows three times more features to be detected compared to the classical full m/z range method.