Journal of breath research最新文献

Pulmonary embolism (PE) can be a diagnostic challenge. Current diagnostic markers for PE are unspecific and new diagnostic tools are needed. The air we exhale is a possible new source for biomarkers which can be tapped into by analysing the exhaled breath condensate (EBC). We analysed the EBC from patients with PE and controls to investigate if the EBC is a useful source for new diagnostic biomarkers of PE. We collected and analysed EBC samples from patients with suspected PE and controls matched on age and sex. Patients in whom PE was ruled out after diagnostic work-up were included in the control group to increase the sensitivity and generalizability of the identified markers. EBC samples were collected using an RTube™. The protein composition of the EBCs were analysed using data dependent label-free quantitative nano liquid chromatography-tandem mass spectrometry. EBC samples from 28 patients with confirmed PE, and 49 controls were analysed. A total of 928 EBC proteins were identified in the 77 EBC samples. As expected, a low protein concentration was determined which resulted in many proteins with unmeasurable levels in several samples. The levels of HSPA5, PEBP1 and SFTPA2 were higher and levels of POF1B, EPPK1, PSMA4, ALDOA, and CFL1 were lower in PE compared with controls. In conclusion, the human EBC contained a variety of endogenous proteins and may be a source for new diagnostic markers of PE and other diseases.

Volatilomics is the branch of metabolomics dedicated to the analysis of volatile organic compounds in exhaled breath for medical diagnostic or therapeutic monitoring purposes. Real-time mass spectrometry (MS) technologies such as proton transfer reaction (PTR) MS are commonly used, and data normalisation is an important step to discard unwanted variation from non-biological sources, as batch effects and loss of sensitivity over time may be observed. As normalisation methods for real-time breath analysis have been poorly investigated, we aimed to benchmark known metabolomic data normalisation methods and apply them to PTR-MS data analysis. We compared seven normalisation methods, five statistically based and two using multiple standard metabolites, on two datasets from clinical trials for COVID-19 diagnosis in patients from the emergency department or intensive care unit. We evaluated different means of feature selection to select the standard metabolites, as well as the use of multiple repeat measurements of ambient air to train the normalisation methods. We show that the normalisation tools can correct for time-dependent drift. The methods that provided the best corrections for both cohorts were probabilistic quotient normalisation and normalisation using optimal selection of multiple internal standards. Normalisation also improved the diagnostic performance of the machine learning models, significantly increasing sensitivity, specificity and area under the receiver operating characteristic (ROC) curve for the diagnosis of COVID-19. Our results highlight the importance of adding an appropriate normalisation step during the processing of PTR-MS data, which allows significant improvements in the predictive performance of statistical models.Clinical trials: VOC-COVID-Diag (EudraCT 2020-A02682-37); RECORDS trial (EudraCT 2020-000296-21).

Allergy is a systemic inflammation; therefore, although the allergic symptom may be seen in a specific organ system, the effects of this inflammation may be seen in other organs. interleukin (IL) IL4, IL5 and IL13 are the major Th2 cytokines and e-cadherin is an epithelial barrier protein. The objective of this research was to assess indicators of inflammation specific to Th2 responses and proteins related to the protective barrier of the airway's inner lining. These assessments were conducted using exhaled breath condensate (EBC), which provides insights into peripheral airway conditions of children suffering from food allergies. The study had 24 patients with food allergy and 24 control individuals younger than three years of age with no history of food reaction. The diagnosis of food allergy was based on food allergen-specific IgE and skin prick test positivity in our clinic and oral food testing in selected cases. EBC samples were obtained by Ecoscreen (Jaegar, Hoechberg, Germany). IL4, IL5, IL13 and E-cadherin levels were measured in these samples by enzyme linked immunoassay. The group of children with food allergies, consisting mainly of 14 girls, had a median age of 16 months, whereas the control group, which included 11 girls, had a median age of 15 months (p= 0.89). Comparing the two groups, children with food allergies exhibited notably lower levels of IL-13 in the EBC compared to the control group (median values of 59.14 and 76.36, respectively,p= 0.02). Conversely, the concentration of IL-4 in the EBC was significantly higher in children with food allergies (median values of 1.94 and 1.29, respectively,p= 0.003). However, the levels of IL-5 and e-cadherin showed no significant differences between the two groups (withp-values of 0.74 and 0.09, respectively) as shown in table1. High level of IL-4 despite the low level of IL-13 in the EBC of children having food allergy may be indicative of an early inflammatory phase that is not yet in the effector phase. Studies about the evolution of this process later in life are needed to assess the role of airway inflammation in children with food allergy who develop asthma.

Pulmonary function is usually assessed by measuring Vital Capacity (VC) using equipment such as a spirometer or ventilometer, but these are not always available to the population, as they are relatively expensive tests, difficult to transport and require trained professionals. However, the single breath counting technique (SBCT) appears as a possible alternative to respiratory function tests, to help in the pathophysiological understanding of lung diseases. The objective is to verify the applicability of the SBCT as a parameter for evaluating VC. This is a systematic review registered in the International Prospective Register of Systematic Reviews (CRD42023383706) and used for PubMed^®, Scientific Electronic Library Online, LILACS, EMBASE, and Web of Science databases of articles published until January 2023. Methodological quality regarding the risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies-2 and National Institutes of Health tools. Eleven of a total of 574 studies were included, of these, nine showed a correlation between VC and SBCT (weak in healthy, moderate in neuromuscular and strong in hospitalized patients). One study of hospitalized patients accurately identified a count value of 21 for a VC of 20 ml kg^-1(Sensitivity = 94% and Specificity = 77%), and another estimated a count lower than 41 for a VC below 80% of predicted in patients with neuromuscular dystrophy (Sensitivity = 89% and Specificity = 62%), and another showed good intra and inter-examiner reproducibility in young, adult, and elderly populations. A meta-analysis of three studies showed a moderate correlation in subjects with neuromuscular diseases (r= 0.62, 95% CI = 0.52-0.71,p< 0.01). A high risk of bias was identified regarding the justification of the sample size and blinding of the evaluators. SBCT has been presented as an alternative to assess VC in the absence of specific equipment. There is a clear relationship between SBCT and VC, especially in neuromuscular and hospitalized individuals. New validation studies conducted with greater control of potential bias risks are necessary.

A 23-subject feasibility study is reported to assess how UV absorbance measurements on exhaled breath samples collected from silicon microreactors can be used to detect COVID-19. The silicon microreactor technology chemoselectively preconcentrates exhaled carbonyl volatile organic compounds and subsequent methanol elution provides samples for analysis. The underlying scientific rationale that viral infection will induce an increase in exhaled carbonyls appears to be supported by the results of the feasibility study. The data indicate statistically significant differences in measured UV absorbance values between healthy and symptomatic COVID-19 positive subjects in the wavelength range from 235 nm to 305 nm. Factors such as subject age were noted as potential confounding variables.

Exhaled breath contains numerous volatile organic compounds (VOCs) known to be related to lung disease like asthma. Its collection is non-invasive, simple to perform and therefore an attractive method for the use even in young children. We analysed breath in children of the multicenter All Age Asthma Cohort (ALLIANCE) to evaluate if 'breathomics' have the potential to phenotype patients with asthma and wheeze, and to identify extrinsic risk factors for underlying disease mechanisms. A breath sample was collected from 142 children (asthma: 51, pre-school wheezers: 55, healthy controls: 36) and analysed using gas chromatography-mass spectrometry (GC/MS). Children were diagnosed according to Global Initiative for Asthma guidelines and comprehensively examined each year over up to seven years. Forty children repeated the breath collection after 24 or 48 months. Most breath VOCs differing between groups reflect the exposome of the children. We observed lower levels of lifestyle-related VOCs and higher levels of the environmental pollutants, especially naphthalene, in children with asthma or wheeze. Naphthalene was also higher in symptomatic patients and in wheezers with recent inhaled corticosteroid use. No relationships with lung function or TH2 inflammation were detected. Increased levels of naphthalene in asthmatics and wheezers and the relationship to disease severity could indicate a role of environmental or indoor air pollution for the development or progress of asthma. Breath VOCs might help to elucidate the role of the exposome for the development of asthma. The study was registered at ClinicalTrials.gov (NCT02496468).

Human studies provide valuable information on components or analytes recovered from exhaled breath, but there are limitations due to inter-individual and intra-individual variation. Future development and implementation of breath tests based on aerosol analysis require a clear understanding of how human factors interact with device geometry to influence particle transport and deposition. The computational fluid and particle dynamics (CFPD) algorithm combines (i) the Eulerian approach to fluid dynamics and (ii) the Lagrangian approach to single particle transport and deposition to predict how particles are carried in fluids and deposited on surfaces. In this work, we developed a 3D multiscale CFPD model to provide insight into human factors that could be important to control or measure during sampling. We designed the model to characterize the local transport, spatial distribution, and deposition of polydisperse particles in a single impaction filter of a commercial aerosol collection device. We highlight the use of decoupling numerical strategies to simultaneously quantify the influence of filter geometry, fluid flowrate, and particle size. Our numerical models showed the remarkable effect of flowrate on aerosol dynamics. Specifically, aerosol mass deposition, spatial distribution, and deposition mechanisms inside the filter. This work as well as future studies on the effect of filter geometry and human factors on aerosol collection will guide the development, standardization, and validation of breath sampling protocols for current and emerging breath tests for forensic and clinical applications.

Nitric oxide has different roles in asthma as both an endogenous modulator of airway function and a pro-inflammatory mediator. Fractional exhaled nitric oxide (FeNO) is a reliable, quantitative, non-invasive, simple, and safe biomarker for assessing airways inflammation in asthma. Previous genome-wide and genetic association studies have shown that different genes and single nucleotide polymorphisms (SNPs) are linked to FeNO. We aimed at identifying SNPs in candidate genes or gene regions that are associated with FeNO in asthma. We evaluated 264 asthma cases (median age 42.8 years, female 47.7%) who had been identified in the general adult population within the Gene Environment Interactions in Respiratory Diseases survey in Verona (Italy; 2008-2010). Two hundred and twenty-one tag-SNPs, which are representative of 50 candidate genes, were genotyped by a custom GoldenGate Genotyping Assay. A two-step association analysis was performed without assuming ana priorigenetic model: step (1) a machine learning technique [gradient boosting machine (GBM)] was used to select the 15 SNPs with the highest variable importance measure; step (2) the GBM-selected SNPs were jointly tested in a linear regression model with natural log-transformed FeNO as the normally distributed outcome and with age, sex, and the SNPs as covariates. We replicated our results within an independent sample of 296 patients from the European Community Respiratory Health Survey III. We found that SNP rs987314 in family with sequence similarity 13 member A (FAM13A) and SNP rs3218258 in interleukin 2 receptor subunit beta (IL2RB) gene regions are significantly associated with FeNO in adult subjects with asthma. These genes are involved in different mechanisms that affect smooth muscle constriction and endothelial barrier function responses (FAM13A), or in immune response processes (IL2RB). Our findings contribute to the current knowledge on FeNO in asthma by identifying two novel SNPs associated with this biomarker of airways inflammation.