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

Volatilome and machine learning in ischemic heart disease: Current challenges and future perspectives

Integrating exhaled breath analysis into the diagnosis of cardiovascular diseases holds significant promise as a valuable tool for future clinical use, particularly for ischemic heart disease (IHD). However, current research on the volatilome (exhaled breath composition) in heart disease remains underexplored and lacks sufficient evidence to confirm its clinical validity. Key challenges hindering the application of breath analysis in diagnosing IHD include the scarcity of studies (only three published papers to date), substantial methodological bias in two of these studies, and the absence of standardized protocols for clinical implementation. Additionally, inconsistencies in methodologies—such as sample collection, analytical techniques, machine learning (ML) approaches, and result interpretation—vary widely across studies, further complicating their reproducibility and comparability. To address these gaps, there is an urgent need to establish unified guidelines that define best practices for breath sample collection, data analysis, ML integration, and biomarker annotation. Until these challenges are systematically resolved, the widespread adoption of exhaled breath analysis as a reliable diagnostic tool for IHD remains a distant goal rather than an imminent reality.

Uncovering Non-Invasive Biomarkers in Paediatric Severe Acute Asthma Using Targeted Exhaled Breath Analysis

BACKGROUND

Severe acute asthma (SAA) in children can be life-threatening. There has been a significant rise in paediatric intensive care unit (PICU) admissions due to SAA over the past two decades. While asthma is a heterogeneous disease, its underlying pathophysiological pathways remain underexplored. This study aimed to assess the value of non-invasive targeted exhaled breath metabolomics analysis to better characterise SAA.

METHODS

Breath samples from 17 children admitted to the PICU with SAA (cases) and 27 children with controlled severe asthma (controls) were analysed using thermal desorption gas chromatography-mass spectrometry (TD-GC-MS).

RESULTS

A targeted volatile organic compound (VOC) analysis identified 25 compounds, of which 16 were shared between groups. Four VOCs were significantly more often present in SAA, and nine VOCs exhibited higher concentrations in SAA. Longitudinal analysis of VOCs from follow-up samples of 10 cases showed no significant temporal differences, reinforcing the reproducibility of identified biomarkers.

CONCLUSIONS

This study exemplifies the potential of exhaled breath analysis to provide insights into the molecular background of SAA. Breath metabolomics may enable early recognition of severe asthma attacks and preventive therapeutic interventions in children with severe asthma.

Effect of H2O2 induced oxidative stress on volatile organic compounds in differentiated 3T3-L1 cells

Oxidative stress (OS) refers to the disruption in the balance between free radical generation and antioxidant defenses, leading to potential tissue damage. Reactive oxygen species (ROS) can interact with biological components, triggering processes like protein oxidation, lipid peroxidation, or DNA damage, resulting in the generation of several volatile organic compounds (VOCs). Recently, VOCs provided new insight into cellular metabolism and can serve as potential biomarkers. The objective is to investigate the impact of OS on cell metabolism by analyzing the release or alterations of VOCs in the headspace of differentiated 3T3-L1 adipocytes. An OS model in differentiated 3T3-L1 cell lines was constructed using hydrogen peroxide (H2O2) treatment. The effect of OS on cell metabolism was analyzed by detecting VOCs in the headspace of the cells using solid phase micro extraction (SPME) and gas chromatography-mass spectrometry (GCMS). Our findings indicate that H2O2 concentrations exceeding 300 µM induce significant OS, leading to adipocyte apoptosis, as evidenced by various assays. Of the twenty VOCs identified, ten were upregulated in the cells. VOCs such as diphenyl ether, 1,3,5-trioxane, 5-methyl tridecane, 2-ethyl-1-hexanol, and 2,4-di-tert-butyl phenol emerged as potential biomarkers for OS. This study demonstrates that elevated OS alters VOC profiles in differentiated 3T3-L1 adipocytes, providing insights into the effects of OS on adipose tissue and identifying potential OS biomarkers.

Review of cancer cell volatile organic compounds: their metabolism and evolution

Cancer is ranked as the top cause of premature mortality. Volatile organic compounds (VOCs) are produced from catalytic peroxidation by reactive oxygen species (ROS) and have become a highly attractive non-invasive cancer screening approach. For future clinical applications, however, the correlation between cancer hallmarks and cancer-specific VOCs requires further study. This review discusses and compares cellular metabolism, signal transduction as well as mitochondrial metabolite translocation in view of cancer evolution and the basic biology of VOCs production. Certain cancerous characteristics as well as the origin of the ROS removal system date back to procaryotes and early eukaryotes and share commonalities with non-cancerous proliferative cells. This calls for future studies on metabolic cross talks and regulation of the VOCs production pathway.

Breath Markers of Oxidative Stress in Children with Severe Viral Lower Respiratory Tract Infection

Severe viral lower respiratory tract infection (LRTI), resulting in both acute and long-term pulmonary disease, constitutes a substantial burden among young children. Viral LRTI triggers local oxidative stress pathways by infection and inflammation, and supportive care in the pediatric intensive care unit may further aggravate oxidative injury. The main goal of this exploratory study was to identify and monitor breath markers linked to oxidative stress in children over the disease course of severe viral LRTI. Exhaled breath was sampled during invasive ventilation, and volatile organic compounds (VOCs) were analyzed using gas chromatography and mass spectrometry. VOCs were selected in an untargeted principal component analysis and assessed for change over time. In addition, identified VOCs were correlated with clinical parameters. Seventy breath samples from 21 patients were analyzed. A total of 15 VOCs were identified that contributed the most to the explained variance of breath markers. Of these 15 VOCs, 10 were previously linked to pathways of oxidative stress. Eight VOCs, including seven alkanes and methyl alkanes, significantly decreased from the initial phase of ventilation to the day of extubation. No correlation was observed with the administered oxygen dose, whereas six VOCs showed a poor to strong positive correlation with driving pressure. In this prospective study of children with severe viral LRTI, the majority of VOCs that were most important for the explained variance mirrored clinical improvement. These breath markers could potentially help monitor the pulmonary oxidative status in these patients, but further research with other objective measures of pulmonary injury is required.

HS-GC-MS analysis of volatile organic compounds after hyperoxia-induced oxidative stress: a validation study

BACKGROUND

Exhaled volatile organic compounds (VOCs), particularly hydrocarbons from oxidative stress-induced lipid peroxidation, are associated with hyperoxia exposure. However, important heterogeneity amongst identified VOCs and concerns about their precise pathophysiological origins warrant translational studies assessing their validity as a marker of hyperoxia-induced oxidative stress. Therefore, this study sought to examine changes in VOCs previously associated with the oxidative stress response in hyperoxia-exposed lung epithelial cells.

METHODS

A549 alveolar epithelial cells were exposed to hyperoxia for 24 h, or to room air as normoxia controls, or hydrogen peroxide as oxidative-stress positive controls. VOCs were sampled from the headspace, analysed by gas chromatography coupled with mass spectrometry and compared by targeted and untargeted analyses. A secondary analysis of breath samples from a large cohort of critically ill adult patients assessed the association of identified VOCs with clinical oxygen exposure.

RESULTS

Following cellular hyperoxia exposure, none of the targeted VOCs, previously proposed as breath markers of oxidative stress, were increased, and decane was significantly decreased. Untargeted analysis did not reveal novel identifiable hyperoxia-associated VOCs. Within the clinical cohort, three previously proposed breath markers of oxidative stress, hexane, octane, and decane had no real diagnostic value in discriminating patients exposed to hyperoxia.

CONCLUSIONS

Hyperoxia exposure of alveolar epithelial cells did not result in an increase in identifiable VOCs, whilst VOCs previously linked to oxidative stress were not associated with oxygen exposure in a cohort of critically ill patients. These findings suggest that the pathophysiological origin of previously proposed breath markers of oxidative stress is more complex than just oxidative stress from hyperoxia at the lung epithelial cellular level.

The optimization and comparison of two high-throughput faecal headspace sampling platforms: the microchamber/thermal extractor and hi-capacity sorptive extraction probes (HiSorb)

Disease detection and monitoring using volatile organic compounds (VOCs) is becoming increasingly popular. For a variety of (gastrointestinal) diseases the microbiome should be considered. As its output is to large extent volatile, faecal volatilomics carries great potential. One technical limitation is that current faecal headspace analysis requires specialized instrumentation which is costly and typically does not work in harmony with thermal desorption units often utilized in e.g. exhaled breath studies. This lack of harmonization hinders uptake of such analyses by the Volatilomics community. Therefore, this study optimized and compared two recently harmonized faecal headspace sampling platforms:High-capacity Sorptive extraction (HiSorb) probesand theMicrochamber thermal extractor (Microchamber). Statistical design of experiment was applied to find optimal sampling conditions by maximizing reproducibility, the number of VOCs detected, and between subject variation. To foster general applicability those factors were defined using semi-targeted as well as untargeted metabolic profiles. HiSorb probes were found to result in a faster sampling procedure, higher number of detected VOCs, and higher stability. The headspace collection using the Microchamber resulted in a lower number of detected VOCs, longer sampling times and decreased stability despite a smaller number of interfering VOCs and no background signals. Based on the observed profiles, recommendations are provided on pre-processing and study design when using either one of both platforms. Both can be used to perform faecal headspace collection, but altogether HiSorb is recommended.

Early Detection of Prostate Cancer: The Role of Scent

Prostate cancer (PCa) represents the cause of the second highest number of cancer-related deaths worldwide, and its clinical presentation can range from slow-growing to rapidly spreading metastatic disease. As the characteristics of most cases of PCa remains incompletely understood, it is crucial to identify new biomarkers that can aid in early detection. Despite the prostate-specific antigen serum (PSA) levels, prostate biopsy, and imaging representing the actual gold-standard for diagnosing PCa, analyzing volatile organic compounds (VOCs) has emerged as a promising new frontier. We and other authors have reported that highly trained dogs can recognize specific VOCs associated with PCa with high accuracy. However, using dogs in clinical practice has several limitations. To exploit the potential of VOCs, an electronic nose (eNose) that mimics the dog olfactory system and can potentially be used in clinical practice was designed. To explore the eNose as an alternative to dogs in diagnosing PCa, we conducted a systematic literature review and meta-analysis of available studies. PRISMA guidelines were used for the identification, screening, eligibility, and selection process. We included six studies that employed trained dogs and found that the pooled diagnostic sensitivity was 0.87 (95% CI 0.86–0.89; I2, 98.6%), the diagnostic specificity was 0.83 (95% CI 0.80–0.85; I2, 98.1%), and the area under the summary receiver operating characteristic curve (sROC) was 0.64 (standard error, 0.25). We also analyzed five studies that used an eNose to diagnose PCa and found that the pooled diagnostic sensitivity was 0.84 (95% CI, 0.80–0.88; I2, 57.1%), the diagnostic specificity was 0.88 (95% CI, 0.84–0.91; I2, 66%), and the area under the sROC was 0.93 (standard error, 0.03). These pooled results suggest that while highly trained dogs have the potentiality to diagnose PCa, the ability is primarily related to olfactory physiology and training methodology. The adoption of advanced analytical techniques, such as eNose, poses a significant challenge in the field of clinical practice due to their growing effectiveness. Nevertheless, the presence of limitations and the requirement for meticulous study design continue to present challenges when employing eNoses for the diagnosis of PCa.

Influence of bacterial and alveolar cell co-culture on microbial VOC production using HS-GC/MS

Volatile organic compounds (VOCs) found in exhaled breath continue to garner interest as an alternative diagnostic tool in pulmonary infections yet, their clinical integration remains a challenge with difficulties in translating identified biomarkers. Alterations in bacterial metabolism secondary to host nutritional availability may explain this but is often inadequately modelled in vitro. The influence of more clinically relevant nutrients on VOC production for two common respiratory pathogens was investigated. VOCs from Staphylococcus aureus (S.aureus) and Pseudomonas aeruginosa (P.aeruginosa) cultured with and without human alveolar A549 epithelial cells were analyzed using headspace extraction coupled with gas chromatography-mass spectrometry. Untargeted and targeted analyses were performed, volatile molecules identified from published data, and the differences in VOC production evaluated. Principal component analysis (PCA) could differentiate alveolar cells from either S. aureus or P. aeruginosa when cultured in isolation based on PC1 (p = 0.0017 and 0.0498, respectively). However, this separation was lost for S. aureus (p = 0.31) but not for P. aeruginosa (p = 0.028) when they were cultured with alveolar cells. S. aureus cultured with alveolar cells led to higher concentrations of two candidate biomarkers, 3-methyl-1-butanol (p = 0.001) and 3-methylbutanal (p = 0.002) when compared to S. aureus, alone. P. aeruginosa metabolism resulted in less generation of pathogen-associated VOCs when co-cultured with alveolar cells compared to culturing in isolation. VOC biomarkers previously considered indicative of bacterial presence are influenced by the local nutritional environment and this should be considered when evaluating their biochemical origin.