Exhaled breath volatile alterations in pregnancy assessed with electronic nose

Detection of lung cancer and stages via breath analysis using a self-made electronic nose device

BACKGROUND

Breathomics is an emerging area focusing on monitoring and diagnosing pulmonary diseases, especially lung cancer. This research aims to employ metabolomic methods to create a breathprint in human-expelled air to rapidly identify lung cancer and its stages.

RESEARCH DESIGN AND METHODS

An electronic nose (e-nose) system with five metal oxide semiconductor (MOS) gas sensors, a microcontroller, and machine learning algorithms was designed and developed for this application. The volunteers in this study include 114 patients with lung cancer and 147 healthy controls to understand the clinical potential of the e-nose system to detect lung cancer and its stages.

RESULTS

In the training phase, in discriminating lung cancer from controls, the XGBoost classifier model with 10-fold cross-validation gave an accuracy of 91.67%. In the validation phase, the XGBoost classifier model correctly identified 35 out of 42 patients with lung cancer samples and 44 out of 51 healthy control samples providing an overall sensitivity of 83.33% and specificity of 86.27%.

CONCLUSIONS

These results indicate that the exhaled breath VOC analysis method may be developed as a new diagnostic tool for lung cancer detection. The advantages of e-nose based diagnostics, such as an easy and painless method of sampling, and low-cost procedures, will make it an excellent diagnostic method in the future.

Exhaled Biomarkers for Point-of-Care Diagnosis: Recent Advances and New Challenges in Breathomics

Cancers, chronic diseases and respiratory infections are major causes of mortality and present diagnostic and therapeutic challenges for health care. There is an unmet medical need for non-invasive, easy-to-use biomarkers for the early diagnosis, phenotyping, predicting and monitoring of the therapeutic responses of these disorders. Exhaled breath sampling is an attractive choice that has gained attention in recent years. Exhaled nitric oxide measurement used as a predictive biomarker of the response to anti-eosinophil therapy in severe asthma has paved the way for other exhaled breath biomarkers. Advances in laser and nanosensor technologies and spectrometry together with widespread use of algorithms and artificial intelligence have facilitated research on volatile organic compounds and artificial olfaction systems to develop new exhaled biomarkers. We aim to provide an overview of the recent advances in and challenges of exhaled biomarker measurements with an emphasis on the applicability of their measurement as a non-invasive, point-of-care diagnostic and monitoring tool.

Noninvasive detection of COPD and Lung Cancer through breath analysis using MOS Sensor array based e-nose

INTRODUCTION

This paper describes the research work done toward the development of a breath analyzing electronic nose (e-nose), and the results obtained from testing patients with lung cancer, patients with chronic obstructive pulmonary disease (COPD), and healthy controls. Pulmonary diseases like COPD and lung cancer are detected with MOS sensor array-based e-noses. The e-nose device with the sensor array, data acquisition system, and pattern recognition can detect the variations of volatile organic compounds (VOC) present in the expelled breath of patients and healthy controls.

MATERIALS AND METHODS

This work presents the e-nose equipment design, study subjects selection, breath sampling procedures, and various data analysis tools. The developed e-nose system is tested in 40 patients with lung cancer, 48 patients with COPD, and 90 healthy controls.

RESULTS

In differentiating lung cancer and COPD from controls, support vector machine (SVM) with 3-fold cross-validation outperformed all other classifiers with an accuracy of 92.3% in cross-validation. In external validation, the same discrimination was achieved by k-nearest neighbors (k-NN) with 75.0% accuracy.

CONCLUSION

The reported results show that the VOC analysis with an e-nose system holds exceptional possibilities in noninvasive disease diagnosis applications.

The Role of Electronic Noses in Phenotyping Patients with Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease (COPD) is a common progressive disorder of the respiratory system which is currently the third leading cause of death worldwide. Exhaled breath analysis is a non-invasive method to study lung diseases, and electronic noses have been extensively used in breath research. Studies with electronic noses have proved that the pattern of exhaled volatile organic compounds is different in COPD. More recent investigations have reported that electronic noses could potentially distinguish different endotypes (i.e., neutrophilic vs. eosinophilic) and are able to detect microorganisms in the airways responsible for exacerbations. This article will review the published literature on electronic noses and COPD and help in identifying methodological, physiological, and disease-related factors which could affect the results.

Human volatilome analysis using eNose to assess uncontrolled asthma in a clinical setting

BACKGROUND

Analyses of exhaled volatile organic compounds (VOCs) have shown promising results when distinguishing individuals with asthma. Currently, there are no biomarkers for uncontrolled asthma. Therefore, we aimed to assess, in a real-life clinical setting, the ability of the exhaled VOC analysis, using an electronic nose (eNose), to identify individuals with uncontrolled asthma.

METHODS

A cross-sectional study was conducted, and breath samples from 199 participants (130 females, aged 6-78, 66% with asthma) were analysed using an eNose. A multivariate unsupervised cluster analysis, using the resistance data from 32 sensors, could distinguish three clusters of VOC patterns in the training and testing groups. Comparisons between the clusters were performed using the one-way ANOVA, Kruskal-Wallis and chi-squared tests.

RESULTS

In the training set (n = 121), three different clusters covering asthma, lung function, symptoms in the previous 4 weeks and age were identified. The pairwise comparisons showed significant differences with respect to chest tightness during exercise, dyspnoea and gender. These findings were confirmed in the testing set (n = 78) where the training model identified three clusters. The participants who reported fewer respiratory symptoms (dyspnoea and night-time awakenings) were grouped into one cluster, while the others comprised participants who showed similar poor control over symptoms with the distribution of the individuals with asthma being significantly different between them.

CONCLUSIONS

In a clinical setting, the analysis of the exhaled VOC profiles using an eNose could be used as a fast and noninvasive complementary assessment tool for the detection of uncontrolled asthma symptoms.

The ovarian cycle may influence the exhaled volatile organic compound profile analyzed by an electronic nose

INTRODUCTION

We aimed to investigate whether the sex hormone profile during the ovarian cycle in healthy women could affect the volatile organic compound (VOC) profile analyzed by an electronic nose (e-nose).

METHODS

We enrolled 21 healthy, never-smoking, regularly menstruating women who were not taking any medications. A series of exhaled breath measurements were performed on all subjects at predefined intervals (days 1-6, 7-12, 13-19, 20-25 and 26-31; day 1 was the first day of menstruation) during their ovarian cycle and analyzed by an e-nose (Cyranose 320).

RESULTS

By principal component analysis, significant modifications of the exhaled VOC profile were observed over the cycle for principal component 1 (PC1; p = 0.001). In particular, the PC1 value was significantly higher during the premenstrual period and during menstruation compared with the first third of estrogen phase, mid-cycle and the first third of progestational phase (for all parameters p < 0.05 and p < 0.01, respectively). Subsequent linear discriminant analysis confirmed the above findings.

CONCLUSIONS

The ovarian cycle may alter the exhaled VOC pattern and this should be taken into account during serial measurements of these markers in the female population.

A European Respiratory Society technical standard: exhaled biomarkers in lung disease

Breath tests cover the fraction of nitric oxide in expired gas (F_eNO), volatile organic compounds (VOCs), variables in exhaled breath condensate (EBC) and other measurements. For EBC and for F_eNO, official recommendations for standardised procedures are more than 10 years old and there is none for exhaled VOCs and particles. The aim of this document is to provide technical standards and recommendations for sample collection and analytic approaches and to highlight future research priorities in the field. For EBC and F_eNO, new developments and advances in technology have been evaluated in the current document. This report is not intended to provide clinical guidance on disease diagnosis and management.Clinicians and researchers with expertise in exhaled biomarkers were invited to participate. Published studies regarding methodology of breath tests were selected, discussed and evaluated in a consensus-based manner by the Task Force members.Recommendations for standardisation of sampling, analysing and reporting of data and suggestions for research to cover gaps in the evidence have been created and summarised.Application of breath biomarker measurement in a standardised manner will provide comparable results, thereby facilitating the potential use of these biomarkers in clinical practice.

Electronic Nose Technology in Respiratory Diseases

Electronic noses (e-noses) are based on arrays of different sensor types that respond to specific features of an odorant molecule, mostly volatile organic compounds (VOCs). Differently from gas chromatography and mass spectrometry, e-noses can distinguish VOCs spectrum by pattern recognition. E-nose technology has successfully been used in commercial applications, including military, environmental, and food industry. Human-exhaled breath contains a mixture of over 3000 VOCs, which offers the postulate that e-nose technology can have medical applications. Based on the above hypothesis, an increasing number of studies have shown that breath profiling by e-nose could play a role in the diagnosis and/or screening of various respiratory and systemic diseases. The aim of the present study was to review the principal literature on the application of e-nose technology in respiratory diseases.

Exhaled breath analysis by electronic nose in respiratory diseases

Breath analysis via electronic nose is a technique oriented around volatile organic compound (VOC) profiling in exhaled breath for diagnostic and prognostic purposes. This approach, when supported by methodologies for VOC identification, has been often referred to as metabolomics or breathomics. Although breath analysis may have a substantial impact on clinical practice, as it may allow early diagnosis and large-scale screening strategies while being noninvasive and inexpensive, some technical and methodological limitations must be solved, together with crucial interpretative issues. By integrating a review of the currently available literature with more speculative arguments about the potential interpretation and application of VOC analysis, the authors aim to provide an overview of the main relevant aspects of this promising field of research.

D'scent of man: a comparative survey of primate chemosignaling in relation to sex

This article is part of a Special Issue (Chemosignals and Reproduction). As highly visual animals, primates, in general, and Old World species (including humans), in particular, are not immediately recognized for reliance in their daily interactions on olfactory communication. Nevertheless, views on primate olfactory acuity and the pervasiveness of their scent signaling are changing, with increased appreciation for the important role of body odors in primate social and sexual behavior. All major taxonomic groups, from lemurs to humans, are endowed with scent-producing organs, and either deposit or exude a wealth of volatile compounds, many of which are known semiochemicals. This review takes a comparative perspective to illustrate the reproductive context of primate signaling, the relevant information content of their signals, the sexually differentiated investigative responses generated, and the behavioral or physiological consequences of message transmission to both signaler and receiver. Throughout, humans are placed alongside their relatives to illustrate the evolutionary continuum in the sexual selection of primate chemosignals. This ever-growing body of evidence points to a critical role of scent in guiding the social behavior and reproductive function throughout the primate order.

Expiratory flow rate, breath hold and anatomic dead space influence electronic nose ability to detect lung cancer

Background

Electronic noses are composites of nanosensor arrays. Numerous studies showed their potential to detect lung cancer from breath samples by analysing exhaled volatile compound pattern (“breathprint”). Expiratory flow rate, breath hold and inclusion of anatomic dead space may influence the exhaled levels of some volatile compounds; however it has not been fully addressed how these factors affect electronic nose data. Therefore, the aim of the study was to investigate these effects.

Methods

37 healthy subjects (44 ± 14 years) and 27 patients with lung cancer (60 ± 10 years) participated in the study. After deep inhalation through a volatile organic compound filter, subjects exhaled at two different flow rates (50 ml/sec and 75 ml/sec) into Teflon-coated bags. The effect of breath hold was analysed after 10 seconds of deep inhalation. We also studied the effect of anatomic dead space by excluding this fraction and comparing alveolar air to mixed (alveolar + anatomic dead space) air samples. Exhaled air samples were processed with Cyranose 320 electronic nose.

Results

Expiratory flow rate, breath hold and the inclusion of anatomic dead space significantly altered “breathprints” in healthy individuals (p < 0.05), but not in lung cancer (p > 0.05). These factors also influenced the discrimination ability of the electronic nose to detect lung cancer significantly.

Conclusions

We have shown that expiratory flow, breath hold and dead space influence exhaled volatile compound pattern assessed with electronic nose. These findings suggest critical methodological recommendations to standardise sample collections for electronic nose measurements.

Solid-state gas sensors for breath analysis: a review

The analysis of volatile compounds is an efficient method to appraise information about the chemical composition of liquids and solids. This principle is applied to several practical applications, such as food analysis where many important features (e.g. freshness) can be directly inferred from the analysis of volatile compounds. The same approach can also be applied to a human body where the volatile compounds, collected from the skin, the breath or in the headspace of fluids, might contain information that could be used to diagnose several kinds of diseases. In particular, breath is widely studied and many diseases can be potentially detected from breath analysis. The most fascinating property of breath analysis is the non-invasiveness of the sample collection. Solid-state sensors are considered the natural complement to breath analysis, matching the non-invasiveness with typical sensor features such as low-cost, easiness of use, portability, and the integration with the information networks. Sensors based breath analysis is then expected to dramatically extend the diagnostic capabilities enabling the screening of large populations for the early diagnosis of pathologies. In the last years there has been an increased attention to the development of sensors specifically aimed to this purpose. These investigations involve both specific sensors designed to detect individual compounds and non-specific sensors, operated in array configurations, aimed at clustering subjects according to their health conditions. In this paper, the recent significant applications of these sensors to breath analysis are reviewed and discussed.

Exhaled breath condensate pH decreases during exercise-induced bronchoconstriction

BACKGROUND AND OBJECTIVE

Exercise-induced bronchoconstriction (EIB) is the temporary narrowing of the airways caused by physical exercise. Its exact pathophysiology is unclear; however, acute changes in airways pH may play a role. Exhaled breath condensate (EBC) pH was suggested as a surrogate indicator for airway acid-base status, but its value is also affected by volatile molecules and respiratory droplet dilution. The aim of the study was to assess changes in EBC pH during EIB.

METHODS

Twenty-two asthmatics who reported breathlessness following exercise and 16 healthy individuals participated in the study. Lung function test was performed and exhaled breath samples were collected for pH, dilution factor and volatile compound pattern measurements (Cyranose 320) pre-exercise and at 0, 10, 20 and 30 min after physical exercise challenge. Fractional exhaled nitric oxide was measured before exercise.

RESULTS

EIB developed in 13 asthmatic subjects. In these participants, but not in the EIB-negative asthmatics (P = 0.51), EBC pH reduced significantly during exercise (P = 0.01). In addition, changes in EBC pH were related to the degree of bronchospasm in the EIB-positive group (P = 0.01, r = 0.68). Exhaled volatile pattern became altered (P < 0.05) during exercise in all subjects (asthmatics and controls). EBC pH changes were not related to EBC dilution or volatile compound pattern alterations (P > 0.05).

CONCLUSIONS

The development of EIB was related to acute changes of EBC pH, which suggest the role of airway pH decrease in the pathophysiology of EIB. Exercise-induced changes in exhaled biomarkers suggest methodological precautions to avoid physical exercise before performing exhaled breath tests.

Exhaled breath analysis by electronic nose in airways disease. Established issues and key questions

Exhaled air contains many volatile organic compounds (VOCs) that are the result of normal and disease-associated metabolic processes anywhere in the body. Different omics techniques can assess the pattern of these VOCs. One such omics technique suitable for breath analysis is represented by electronic noses (eNoses), providing fingerprints of the exhaled VOCs, called breathprints. Breathprints have been shown to be altered in different disease states, including in asthma and COPD. This review describes the current status on clinical validation and application of breath analysis by electronic noses in the diagnosis and monitoring of chronic airways diseases. Furthermore, important methodological issues including breath sampling, modulating factors and incompatibility between eNoses are raised and discussed. Next steps towards clinical application of electronic noses are provided, including further validation in suspected disease, assessment of the influence of different comorbidities, the value in longitudinal monitoring of patients with asthma and COPD and the possibility to predict treatment responses. Eventually, a Breath Cloud may be constructed, a large database containing disease-specific breathprints. When collaborative efforts are put into optimization of this technique, it can provide a rapid and non-invasive first line diagnostic test.

Lack of heritability of exhaled volatile compound pattern: an electronic nose twin study

Electronic noses can distinguish various disorders by analyzing exhaled volatile organic compound (VOC) pattern; however it is unclear how hereditary and environmental backgrounds affect the exhaled VOC pattern. A twin study enrolling monozygotic (MZ) and dizygotic (DZ) twins is an ideal tool to separate the influence of these factors on the exhaled breath pattern. Exhaled breath samples were collected in duplicates from 28 never smoking twin pairs (in total 112 samples) without lung diseases and processed with an electronic nose (Cyranose 320). Univariate quantitative hereditary modeling (ACE analysis) adjusted for age and gender was performed to decompose the phenotypic variance of the exhaled volatile compound pattern (assessing principal components (PCs) derived from electronic nose data) into hereditary (A), shared (C), and unshared (E) environmental effects. Exhaled VOC pattern showed good intra-subject reproducibility as assessed with the Bland-Altman plot. Significant correlations were found between exhaled VOC patterns of both MZ and DZ twins. The hereditary background did not influence the VOC pattern. The shared environmental effect on PC 1, 2 and 3 was estimated to be 93%, 94% and 54%, respectively. The unshared (unique) environmental influence explained a smaller variance (7%, 6% and 46%). For the first time using the twin design, we have shown that the environmental background largely affects the exhaled volatile compound pattern in never smoking volunteers without respiratory disorders. Further studies should identify these environmental factors and also assess their influence on exhaled breath patterns in patients with lung diseases.

Exhaled biomarker pattern is altered in children with obstructive sleep apnoea syndrome

OBJECTIVES

Obstructive sleep apnoea syndrome (OSAS) is a common disorder in children, which is associated with enhanced inflammatory status. Inflammation-associated changes could be monitored by the assessment of exhaled biomarker profile. This study aimed to compare the exhaled biomarker profile in children with OSAS and habitual snorers.

METHODS

Eighteen children with OSAS (8 ± 2 years, mean ± SD) and ten non-OSAS subjects with habitual snoring (9 ± 2 years) were recruited. Exhaled breath was collected from the lower airways, processed using an electronic nose (E-nose) and analyzed off-line using principal component analysis, followed by discrimination analysis and logistic regression to build a receiver operating characteristic (ROC) curve.

RESULTS

Exhaled biomarker pattern of OSAS patients was discriminated from that of control subjects (p = 0.03, cross-validation accuracy: 64%), ROC curve analysis (area: 0.83) showed 78% sensitivity and 70% specificity.

CONCLUSIONS

The altered exhaled biomarker pattern in OSAS might reflect accelerated airway and/or systemic inflammation in diseased state. Breath pattern analysis by an E-nose can serve as a new tool to monitor inflammation in children with OSAS.

The electronic nose in respiratory medicine

Several volatile organic compounds have been identified in exhaled breath in healthy subjects and patients with respiratory diseases by gas chromatography/mass spectrometry. Identification of selective patterns of volatile organic compounds in exhaled breath could be used as a biomarker of inflammatory lung diseases. An electronic nose (e-nose) is an artificial sensor system that generally consists of an array of chemical sensors for detection of volatile organic compound profiles (breathprints) and an algorithm for pattern recognition. E-noses are handheld, portable devices that provide immediate results. E-noses discriminate between patients with respiratory disease, including asthma, COPD and lung cancer, and healthy control subjects, and also among patients with different respiratory diseases. E-nose breathprints are associated with airway inflammation activity. In combination with other 'omics' platforms, e-nose technology might contribute to the identification of new surrogate markers of pulmonary inflammation and subphenotypes of patients with respiratory diseases, provide a molecular basis to a personalized pharmacological treatment, and facilitate the development of new drugs.

Circulating and exhaled vascular endothelial growth factor in asthmatic pregnancy

CONTEXT

Vascular endothelial growth factor (VEGF) plays a role in asthma and pathological pregnancies.

OBJECTIVE

This is the first study assessing plasma and exhaled breath condensate VEGF levels in asthmatic pregnancy.

MATERIAL AND METHODS

Thirty-one asthmatic pregnant, 29 asthmatic nonpregnant, 28 healthy pregnant and 22 healthy nonpregnant women were enrolled. Plasma was collected in all subjects, EBC in 57 volunteers for VEGF measurements.

RESULTS

Plasma VEGF decreased in both pregnant groups (p < 0.01), without any differences between the asthmatic and the respective nonasthmatic groups (p > 0.05). VEGF was undetectable in EBC.

CONCLUSION

Concomitant asthma does not affect plasma VEGF during pregnancy.