Validation of exhaled volatile organic compounds analysis using electronic nose as index of COPD severity

Clinical applications of volatilomic assays

The study of metabolomics is revealing immense potential for diagnosis, therapy monitoring, and understanding of pathogenesis processes. Volatilomics is a subcategory of metabolomics interested in the detection of molecules that are small enough to be released in the gas phase. Volatile compounds produced by cellular processes are released into the blood and lymph, and can reach the external environment through different pathways, such as the blood-air interface in the lung that are detected in breath, or the blood-water interface in the kidney that leads to volatile compounds detected in urine. Besides breath and urine, additional sources of volatile compounds such as saliva, blood, feces, and skin are available. Volatilomics traces its roots back over fifty years to the pioneering investigations in the 1970s. Despite extensive research, the field remains in its infancy, hindered by a lack of standardization despite ample experimental evidence. The proliferation of analytical instrumentations, sample preparations and methods of volatilome sampling still make it difficult to compare results from different studies and to establish a common standard approach to volatilomics. This review aims to provide an overview of volatilomics' diagnostic potential, focusing on two key technical aspects: sampling and analysis. Sampling poses a challenge due to the susceptibility of human samples to contamination and confounding factors from various sources like the environment and lifestyle. The discussion then delves into targeted and untargeted approaches in volatilomics. Some case studies are presented to exemplify the results obtained so far. Finally, the review concludes with a discussion on the necessary steps to fully integrate volatilomics into clinical practice.

Exhaled volatile organic compounds and lung microbiome in COPD: a pilot randomised controlled trial

Background

Breath analysis is a burgeoning field, with interest in volatile organic compounds (VOCs) as a noninvasive diagnostic tool or an outcome measure, but no randomised controlled trials (RCTs) have yet evaluated this technology in a clinical trial longitudinally. In a pilot RCT, our exploratory objectives were feasibility of measuring VOCs via multiple techniques, assessing relationships between VOCs and Haemophilus colonisation and whether CXCR2 antagonism with danirixin altered lung microbiome composition in individuals with COPD.

Method

43 participants had VOCs and sputum biomarkers evaluated. VOCs and induced sputum were collected after 6 h of fasting at screening and at days 1, 7 and 14. VOCs were analysed via gas chromatography mass spectrometry (GC-MS), field asymmetric ion mobility spectrometry (FAIMS) and eNose. The primary outcome for these analyses was the relationship between VOCs and Haemophilus abundance determined by 16S rRNA sequencing.

Results

A joint-effects model demonstrated a modest relationship between four exhaled VOCs and Haemophilus relative abundance (R²=0.55) measured only by GC-MS, but not as measured using gas chromtaography FAIMS or eNose. There was considerable variability in absolute quantities of individual VOCs longitudinally.

Conclusions

VOC measurement in clinical trials to identify subsets of COPD is feasible, but assessment of new VOC technologies must include concurrent GC-MS validation. Further work to standardise collection of VOCs and measuring a background or “housekeeper” VOC is required to understand and normalise individual VOC quantities.

VOC measurement in clinical trials to identify COPD subsets is feasible, but assessment of VOC technologies must include concurrent GC-MS validation. Further work to standardise collection of VOCs and measure a background or “housekeeper” VOC is required.https://bit.ly/3BNyKvS

The smell of lung disease: a review of the current status of electronic nose technology

There is a need for timely, accurate diagnosis, and personalised management in lung diseases. Exhaled breath reflects inflammatory and metabolic processes in the human body, especially in the lungs. The analysis of exhaled breath using electronic nose (eNose) technology has gained increasing attention in the past years. This technique has great potential to be used in clinical practice as a real-time non-invasive diagnostic tool, and for monitoring disease course and therapeutic effects. To date, multiple eNoses have been developed and evaluated in clinical studies across a wide spectrum of lung diseases, mainly for diagnostic purposes. Heterogeneity in study design, analysis techniques, and differences between eNose devices currently hamper generalization and comparison of study results. Moreover, many pilot studies have been performed, while validation and implementation studies are scarce. These studies are needed before implementation in clinical practice can be realised. This review summarises the technical aspects of available eNose devices and the available evidence for clinical application of eNose technology in different lung diseases. Furthermore, recommendations for future research to pave the way for clinical implementation of eNose technology are provided.

Association between frailty index, lung function, and major clinical determinants in chronic obstructive pulmonary disease

BACKGROUND

Airflow limitation alone is unable to capture the complexity of chronic obstructive pulmonary disease (COPD), better explained by comprehensive disease-specific indexes. Frailty is a clinical condition characterized by high vulnerability to internal and external stressors and represents a strong predictor of adverse outcomes.

AIMS

Primary objective was to test the association between indexes of lung function and COPD severity with frailty index (FI), and secondary to evaluate the association between FI and comorbidities, cognitive and physical function, BODE index, and mortality.

METHODS

150 stable COPD outpatients were enrolled and followed up to 4 years. At baseline, participants performed a geriatric multidimensional assessment, pulmonary function tests, arterial blood gas analysis, 6-min walking test, and bioimpedance analysis. BODE and FI were calculated. Spearman's ρ was used to assess correlations. Mortality was assessed using Kaplan-Meier curves.

RESULTS

Participants were followed up for a median of 39 months. Mean age was 73 years and median frailty index 0.15 (IQR 0.11-0.19). FI was higher in frequent exacerbators (≥ 2/year) (mean 0.18 vs 0.15, p 0.01) and dyspnoeic patients (mMRC ≥ 2) (mean 0.21 vs 0.14, p < 0.01) and correlated with lung volumes, expiratory flows, and pressure of arterial oxygen. FI was positively correlated with the number of comorbidities, depressive symptoms, cognitive decline, and BODE index. Mortality was higher in patients with BODE higher than 3 (HR 3.6, 95% CI 1.2-10.9), and not associated with FI.

DISCUSSION

FI positively correlates with all clinical drivers orienting the choice of treatment in COPD.

CONCLUSIONS

FI associates with lung function and COPD severity, but does not associate with mortality.

A systematic review of the diagnostic accuracy of volatile organic compounds in airway diseases and their relation to markers of type-2 inflammation

BACKGROUND

Asthma and COPD continue to cause considerable diagnostic and treatment stratification challenges. Volatile organic compounds (VOCs) have been proposed as feasible diagnostic and monitoring biomarkers in airway diseases.

AIMS

To 1) conduct a systematic review evaluating the diagnostic accuracy of VOCs in diagnosing airway diseases; 2) understand the relationship between reported VOCs and biomarkers of type-2 inflammation; 3) assess the standardisation of reporting according to STARD and TRIPOD criteria; 4) review current methods of breath sampling and analysis.

METHODS

A PRISMA-oriented systematic search was conducted (January 1997 to December 2020). Search terms included: "asthma", "volatile organic compound(s)", "VOC" and "COPD". Two independent reviewers examined the extracted titles against review objectives.

RESULTS

44 full-text papers were included; 40/44 studies were cross-sectional and four studies were interventional in design; 17/44 studies used sensor-array technologies (e.g. eNose). Cross-study comparison was not possible across identified studies due to the heterogeneity in design. The commonest airway diseases differentiating VOCs belonged to carbonyl-containing classes (i.e. aldehydes, esters and ketones) and hydrocarbons (i.e. alkanes and alkenes). Although individual markers that are associated with clinical biomarkers of type-2 inflammation were recognised (i.e. ethane and 3,7-dimethylnonane for asthma and α-methylstyrene and decane for COPD), these were not consistently identified across studies. Only 3/44 reported following STARD or TRIPOD criteria for diagnostic accuracy and multivariate reporting, respectively.

CONCLUSIONS

Breath VOCs show promise as diagnostic biomarkers of airway diseases and for type-2 inflammation profiling. However, future studies should focus on transparent reporting of diagnostic accuracy and multivariate models and continue to focus on chemical identification of volatile metabolites.

Application of chemoresistive gas sensors and chemometric analysis to differentiate the fingerprints of global volatile organic compounds from diseases. Preliminary results of COPD, lung cancer and breast cancer

BACKGROUND

Analysis of volatile organic compounds (VOCs) in exhaled breath has been proposed as a screening method that discriminates between disease and healthy subjects, few studies evaluate whether these chemical fingerprints are specific when compared between diseases. We evaluated global VOCs and their discrimination capacity in chronic obstructive pulmonary disease (COPD), lung cancer, breast cancer and healthy subjects by chemoresistive sensors and chemometric analysis.

METHODS

A cross-sectional study was conducted with the participation of 30 patients with lung cancer, 50 with breast cancer, 50 with COPD and 50 control subjects. Each participant's exhaled breath was analyzed with the electronic nose. A multivariate analysis was carried: principal component analysis (PCA) and, canonical analysis of principal coordinates (CAP). Twenty single-blind samples from the 4 study groups were evaluated by CAP.

RESULTS

A separation between the groups of patients to the controls was achieved through PCA with explanations of >90% of the data and with a correct classification of 100%. In the CAP of the 4 study groups, discrimination between the diseases was obtained with 2 canonical axes with a correct general classification of 91.35%. This model was used for the prediction of the single-blind samples resulting in correct classification of 100%.

CONCLUSIONS

The application of chemoresistive gas sensors and chemometric analysis can be used as a useful tool for a screening test for lung cancer, breast cancer and COPD since this equipment detects the set of VOCs present in the exhaled breath to generate a characteristic chemical fingerprint of each disease.

Volatile Organic Compounds in Exhaled Breath as Fingerprints of Lung Cancer, Asthma and COPD

Lung cancer, chronic obstructive pulmonary disease (COPD) and asthma are inflammatory diseases that have risen worldwide, posing a major public health issue, encompassing not only physical and psychological morbidity and mortality, but also incurring significant societal costs. The leading cause of death worldwide by cancer is that of the lung, which, in large part, is a result of the disease often not being detected until a late stage. Although COPD and asthma are conditions with considerably lower mortality, they are extremely distressful to people and involve high healthcare overheads. Moreover, for these diseases, diagnostic methods are not only costly but are also invasive, thereby adding to people’s stress. It has been appreciated for many decades that the analysis of trace volatile organic compounds (VOCs) in exhaled breath could potentially provide cheaper, rapid, and non-invasive screening procedures to diagnose and monitor the above diseases of the lung. However, after decades of research associated with breath biomarker discovery, no breath VOC tests are clinically available. Reasons for this include the little consensus as to which breath volatiles (or pattern of volatiles) can be used to discriminate people with lung diseases, and our limited understanding of the biological origin of the identified VOCs. Lung disease diagnosis using breath VOCs is challenging. Nevertheless, the numerous studies of breath volatiles and lung disease provide guidance as to what volatiles need further investigation for use in differential diagnosis, highlight the urgent need for non-invasive clinical breath tests, illustrate the way forward for future studies, and provide significant guidance to achieve the goal of developing non-invasive diagnostic tests for lung disease. This review provides an overview of these issues from evaluating key studies that have been undertaken in the years 2010–2019, in order to present objective and comprehensive updated information that presents the progress that has been made in this field. The potential of this approach is highlighted, while strengths, weaknesses, opportunities, and threats are discussed. This review will be of interest to chemists, biologists, medical doctors and researchers involved in the development of analytical instruments for breath diagnosis.

Potential of the Electronic Nose for the Detection of Respiratory Diseases with and without Infection

Respiratory tract infections are common, and when affecting the lower airways and lungs, can result in significant morbidity and mortality. There is an unfilled need for simple, non-invasive tools that can be used to screen for such infections at the clinical point of care. The electronic nose (eNose) is a novel technology that detects volatile organic compounds (VOCs). Early studies have shown that certain diseases and infections can result in characteristic changes in VOC profiles in the exhaled breath. This review summarizes current knowledge on breath analysis by the electronic nose and its potential for the detection of respiratory diseases with and without infection.

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.

Identification of metabolic markers in patients with type 2 Diabetes by Ultrafast gas chromatography coupled to electronic nose. A pilot study

Metabolomics is a potential tool for the discovery of new biomarkers in the early diagnosis of diseases. An ultra-fast gas chromatography system equipped to an electronic nose detector (FGC eNose) was used to identify the metabolomic profile of Volatile Organic Compounds (VOCs) in type 2 diabetes (T2D) urine from Mexican population. A cross-sectional, comparative, and clinical study with translational approach was performed. We recruited twenty T2D patients and twenty-one healthy subjects. Urine samples were taken and analyzed by FGC eNose. Eighty-eight compounds were identified through Kovats's indexes. A natural variation of 30% between the metabolites, expressed by study groups, was observed in Principal Component 1 and 2 with a significant difference (p < 0.001). The model, performed through a Canonical Analysis of Principal coordinated (CAP), allowed a correct classification of 84.6% between healthy and T2D patients, with a 15.4% error. The metabolites 2-propenal, 2-propanol, butane- 2,3-dione and 2-methylpropanal, were increased in patients with T2D, and they were strongly correlated with discrimination between clinically healthy people and T2D patients. This study identified metabolites in urine through FGC eNose that can be used as biomarkers in the identification of T2D patients. However, more studies are needed for its implementation in clinical practice.

Identification of breath-prints for the COPD detection associated with smoking and household air pollution by electronic nose

PURPOSE

The analysis of breath-print, has been proposed as an attractive alternative to investigate possible biomarkers of Chronic Obstructive Pulmonary Disease (COPD). The aim of the present study was to discriminate between healthy subjects, patients with COPD associated with smoking (COPD-S) and patients with COPD associated with household air pollution (COPD-HAP).

METHODS

A cross-sectional study of 294 participants was conducted, 88 with smoking associated COPD, 28 associated with HAP and 178 healthy subjects. Breath-print analysis was performed by using the Cyranose 320 electronic nose. Group data were evaluated by Principal Component Analysis (PCA), Canonical Discriminant Analysis (CDA) and Support Vector Machine (SVM) and the test's diagnostic power by means of ROC (Receiver Operating Characteristic) curves.

RESULTS

The results indicated that the breath-print of patients with COPD is different from the one of healthy subjects explaining a variability of 93.8% with a correct prediction of 97.8% and correct classification of 100%,also positive and negative predictive value of 96.5 and 100% respectively. Furthermore, the breath-print of exhaled breath from patients with COPD-S and COPD-HAP does not present any difference.

CONCLUSIONS

The breath-print of exhaled breath from patients with COPD-S and COPD-HAP does not present any difference, which demonstrates that the breath-print is related to the disease and not to causality. With these results, the analysis of the breath-print of COPD is proposed as an alternative for a screening method in future clinical applications.

A Low-Cost Breath Analyzer Module in Domiciliary Non-Invasive Mechanical Ventilation for Remote COPD Patient Monitoring

Smart Breath Analyzers were developed as sensing terminals of a telemedicine architecture devoted to remote monitoring of patients suffering from Chronic Obstructive Pulmonary Disease (COPD) and home-assisted by non-invasive mechanical ventilation via respiratory face mask. The devices based on different sensors (CO₂/O₂ and Volatile Organic Compounds (VOCs), relative humidity and temperature (R.H. & T) sensors) monitor the breath air exhaled into the expiratory line of the bi-tube patient breathing circuit during a noninvasive ventilo-therapy session; the sensor raw signals are transmitted pseudonymized to National Health Service units by TCP/IP communication through a cloud remote platform. The work is a proof-of-concept of a sensors-based IoT system with the perspective to check continuously the effectiveness of therapy and/or any state of exacerbation of the disease requiring healthcare. Lab tests in controlled experimental conditions by a gas-mixing bench towards CO₂/O₂ concentrations and exhaled breath collected in a sampling bag were carried out to test the realized prototypes. The Smart Breath Analyzers were also tested in real conditions both on a healthy volunteer subject and a COPD suffering patient.

Exploring the Ability of Electronic Nose Technology to Recognize Interstitial Lung Diseases (ILD) by Non-Invasive Breath Screening of Exhaled Volatile Compounds (VOC): A Pilot Study from the European IPF Registry (eurIPFreg) and Biobank

Background: There is an increasing interest in employing electronic nose technology in the diagnosis and monitoring of lung diseases. Interstitial lung diseases (ILD) are challenging in regard to setting an accurate diagnosis in a timely manner. Thus, there is a high unmet need in non-invasive diagnostic tests. This single-center explorative study aimed to evaluate the usefulness of electronic nose (Aeonose^®) in the diagnosis of ILDs. Methods: Exhaled volatile organic compound (VOC) signatures were obtained by Aeonose^® in 174 ILD patients, 23 patients with chronic obstructive pulmonary disease (COPD), and 33 healthy controls (HC). Results: By dichotomous comparison of VOC’s between ILD, COPD, and HC, a discriminating algorithm was established. In addition, direct analyses between the ILD subgroups, e.g., cryptogenic organizing pneumonia (COP, n = 28), idiopathic pulmonary fibrosis (IPF, n = 51), and connective tissue disease-associated ILD (CTD-ILD, n = 25) were performed. Area under the Curve (AUC) and Matthews’s correlation coefficient (MCC) were used to interpret the data. In direct comparison of the different ILD subgroups to HC, the algorithms developed on the basis of the Aeonose^® signatures allowed safe separation between IPF vs. HC (AUC of 0.95, MCC of 0.73), COP vs. HC (AUC 0.89, MCC 0.67), and CTD-ILD vs. HC (AUC 0.90, MCC 0.69). Additionally, to a case-control study design, the breath patterns of ILD subgroups were compared to each other. Following this approach, the sensitivity and specificity showed a relevant drop, which results in a poorer performance of the algorithm to separate the different ILD subgroups (IPF vs. COP with MCC 0.49, IPF vs. CTD-ILD with MCC 0.55, and COP vs. CT-ILD with MCC 0.40). Conclusions: The Aeonose^® showed some potential in separating ILD subgroups from HC. Unfortunately, when applying the algorithm to distinguish ILD subgroups from each other, the device showed low specificity. We suggest that artificial intelligence or principle compound analysis-based studies of a much broader data set of patients with ILDs may be much better suited to train these devices.

Ultrafast gas chromatography coupled to electronic nose to identify volatile biomarkers in exhaled breath from chronic obstructive pulmonary disease patients: A pilot study

An analytical method to identify volatile organic compounds (VOCs) in the exhaled breath from patients with a diagnosis of chronic obstructive pulmonary disease (COPD) using a ultrafast gas chromatography system equipped with an electronic nose detector (FGC eNose) has been developed. A prospective study was performed in 23 COPD patients and 33 healthy volunteers; exhalation breathing tests were performed with Tedlar bags. Each sample was analyzed by FCG eNose and the identification of VOCs was based on the Kovats index. Raw data were reduced by principal component analysis (PCA) and canonical discriminant analysis [canonical analysis of principal coordinates (CAP)]. The FCG eNose technology was able to identify 17 VOCs that distinguish COPD patients from healthy volunteers. At all stages of PCA and CAP the discrimination between groups was obvious. Chemical prints were correctly classified up to 82.2%, and were matched with 78.9% of the VOCs detected in the exhaled breath samples. Receiver operating characteristic curve analysis indicated the sensitivity and specificity to be 96% and 91%, respectively. This pilot study demonstrates that FGC eNose is a useful tool to identify VOCs as biomarkers in exhaled breath from COPD patients. Further studies should be performed to enhance the clinical relevance of this quick and ease methodology for COPD diagnosis.

Exhaled Breath Analysis in Obstructive Sleep Apnea Syndrome: A Review of the Literature

Background and Objectives: Obstructive sleep apnea syndrome (OSAS) represents an independent risk factor for cardiovascular, metabolic and neurological events. Polysomnography is the gold-standard for the diagnosis, however is expensive and time-consuming and not suitable for widespread use. Breath analysis is an innovative, non-invasive technique, able to provide clinically relevant information about OSAS. This systematic review was aimed to outline available evidence on the role of exhaled breath analysis in OSAS, taking into account the techniques' level of adherence to the recently proposed technical standards. Materials and Methods: Articles reporting original data on exhaled breath analysis in OSAS were identified through a computerized and manual literature search and screened. Duplicate publications, case reports, case series, conference papers, expert opinions, comments, reviews and meta-analysis were excluded. Results: Fractional exhaled Nitric Oxide (FeNO) is higher in OSAS patients than controls, however its absolute value is within reported normal ranges. FeNO association with AHI is controversial, as well as its change after continuous positive airway pressure (C-PAP) therapy. Exhaled breath condensate (EBC) is acid in OSAS, cytokines and oxidative stress markers are elevated, they positively correlate with AHI and normalize after treatment. The analysis of volatile organic compounds (VOCs) by spectrometry or electronic nose is able to discriminate OSAS from healthy controls. The main technical issues regards the dilution of EBC and the lack of external validation in VOCs studies. Conclusions: Exhaled breath analysis has a promising role in the understanding of mechanisms underpinning OSAS and has demonstrated a clinical relevance in identifying individuals affected by the disease, in assessing the response to treatment and, potentially, to monitor patient's adherence to mechanical ventilation. Albeit the majority of the technical standards proposed by the ERS committee have been followed by existing papers, further work is needed to uniform the methodology.

Breath analysis in respiratory diseases: state-of-the-art and future perspectives

INTRODUCTION

The vast majority of respiratory diseases are associated with the production of volatile organic compounds (VOCs), the analysis of which might improve our knowledge about these disorders and their clinical management. The aim of this narrative review is to provide a comprehensive summary of current evidence supporting the application of breath analysis in the field of respiratory diseases, as well as suggesting potential applications available in the near future. Areas covered: A computerized literature search was performed to identify relevant articles reporting original data on the clinical use of breath analysis in respiratory diseases. Papers focusing on diseases other than respiratory, technical issues of VOC sampling and analysis, in vitro experiments or exogenous compounds were excluded. Expert commentary: Currently available evidence on the application of breath analysis in respiratory diseases is encouraging; however, it is mostly based on single-center studies without external validation. The standardization of the technique, together with multicenter clinical trials with external validation, will ensure it is ready for clinical use. Current and new applications in respiratory diseases may represent a major breakthrough in the field, so much so as to deserve further efforts in outlining the most effective way to apply VOC analysis for clinical purposes.

Cluster analysis on breath print of newly diagnosed COPD patients: effects of therapy

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a highly heterogeneous disease and airflow limitation and symptoms only partially capture such heterogeneity. Since COPD is known to affect the production of volatile organic compounds (VOCs), we aimed to verify to which extent exhaled VOCs can characterize newly diagnosed COPD patients and changes in response to inhaled therapy.

MATERIALS AND METHODS

Fifty newly diagnosed COPD patients were consecutively recruited among those attending the pulmonary medicine outpatient clinic at 'Campus Bio-Medico' University Hospital. VOCs were collected using the Pneumopipe^® and analysed by the BIONOTE electronic nose both at baseline and after 12 weeks of inhaled therapy. Patients were grouped using K-mean cluster analysis on BIONOTE responses and the obtained clusters were compared via non-parametric tests.

RESULTS

We identified three clusters of subjects: (a) without remarkable comorbidities; (b) with air trapping and higher BODE index score (mean 1.2); (c) without air trapping and with a lower BODE index. Inhaled bronchodilators caused a quantitative reduction in the amound of VOCs, while inhaled steroids provided a qualitative modification of the breath profile.

CONCLUSION

VOCs patterns categorize newly diagnosed COPD subjects. VOCs production declines after bronchodilators administration and changes in quality after topic steroid treatment.