Diagnostic performance of an electronic nose, fractional exhaled nitric oxide, and lung function testing in asthma

Exhaled breath profiling by electronic nose enabled discrimination of allergic rhinitis and extrinsic asthma

AIM

To assess whether an e-nose could discriminate between subjects affected by allergic rhinitis with and without concomitant extrinsic asthma, as well as from healthy controls, in terms of exhaled VOC-profile.

METHODS

Fourteen patients with Extrinsic Asthma and Allergic Rhinitis (AAR), 14 patients with Allergic Rhinitis without asthma (AR) and 14 healthy controls (HC) participated in a cross-sectional study. Exhaled breath was collected by a standardized method and sampled by an e-nose (Cyranose 320). Raw data were reduced by Principal component analysis and analyzed by canonical discriminant analysis. Cross-validation accuracy (CVA) and Receiver Operating Characteristic(ROC)-curves were calculated. External validation in newly recruited patients (7 AAR, 7 AR and 7 HC) was tested using the previous training model.

RESULTS

Breathprints of patients with AR clustered from those with AAR (CVA = 85.7%), as well as HC (CVA = 82.1%). Breathprints from AAR were also separated from those of HC (CVA = 75.0%). External validation confirmed the above findings.

CONCLUSIONS

An e-nose can discriminate exhaled breath from subjects with allergic rhinitis with and without extrinsic asthma, which represent two different diseases with partly overlapping features. This supports the view of using breath profiling to diagnose asthma also in patients with allergic rhinitis.

Precision Medicine in Targeted Therapies for Severe Asthma: Is There Any Place for "Omics" Technology?

According to the current guidelines, severe asthma still represents a controversial topic in terms of definition and management. The introduction of novel biological therapies as a treatment option for severe asthmatic patients paved the way to a personalized approach, which aims at matching the appropriate therapy with the different asthma phenotypes. Traditional asthma phenotypes have been decomposing by an increasing number of asthma subclasses based on functional and physiopathological mechanisms. This is possible thanks to the development and application of different omics technologies. The new asthma classification patterns, particularly concerning severe asthma, include an increasing number of endotypes that have been identified using new omics technologies. The identification of endotypes provides new opportunities for the management of asthma symptoms, but this implies that biological therapies which target inflammatory mediators in the frame of specific patterns of inflammation should be developed. However, the pathway leading to a precision approach in asthma treatment is still at its beginning. The aim of this review is providing a synthetic overview of the current asthma management, with a particular focus on severe asthma, in the light of phenotype and endotype approach, and summarizing the current knowledge about "omics" science and their therapeutic relevance in the field of bronchial asthma.

Breathomics for Assessing the Effects of Treatment and Withdrawal With Inhaled Beclomethasone/Formoterol in Patients With COPD

Background: Prospective pharmacological studies on breathomics profiles in COPD patients have not been previously reported. We assessed the effects of treatment and withdrawal of an extrafine inhaled corticosteroid (ICS)-long-acting β₂-agonist (LABA) fixed dose combination (FDC) using a multidimensional classification model including breathomics.

Methods: A pilot, proof-of-concept, pharmacological study was undertaken in 14 COPD patients on maintenance treatment with inhaled fluticasone propionate/salmeterol (500/50 μg b.i.d.) for at least 8 weeks (visit 1). Patients received 2-week treatment with inhaled beclomethasone dipropionate/formoterol (100/6 μg b.i.d.) (visit 2), 4-week treatment with formoterol alone (6 μg b.i.d.) (visit 3), and 4-week treatment with beclomethasone/formoterol (100/6 μg b.i.d.) (visit 4). Exhaled breath analysis with two e-noses, based on different technologies, and exhaled breath condensate (EBC) NMR-based metabolomics were performed. Sputum cell counts, sputum supernatant and EBC prostaglandin E₂ (PGE₂) and 15-F_2t-isoprostane, fraction of exhaled nitric oxide, and spirometry were measured.

Results: Compared with formoterol alone, EBC acetate and sputum PGE₂, reflecting airway inflammation, were reduced after 4-week beclomethasone/formoterol. Three independent breathomics techniques showed that extrafine beclomethasone/formoterol short-term treatment was associated with different breathprints compared with regular fluticasone propionate/salmeterol. Either ICS/LABA FDC vs. formoterol alone was associated with increased pre-bronchodilator FEF_25−75% and FEV₁/FVC (P = 0.008–0.029). The multidimensional model distinguished fluticasone propionate/salmeterol vs. beclomethasone/formoterol, fluticasone propionate/salmeterol vs. formoterol, and formoterol vs. beclomethasone/formoterol (accuracy > 70%, P < 0.01).

Conclusions: Breathomics could be used for assessing ICS treatment and withdrawal in COPD patients. Large, controlled, prospective pharmacological trials are required to clarify the biological implications of breathomics changes. EUDRACT number: 2012-001749-42.

Breathprinting and Early Diagnosis of Lung Cancer

The electronic nose (e-nose) is a promising technology as a useful addition to the currently available modalities to achieve lung cancer diagnosis. The e-nose can assess the volatile organic compounds detected in the breath and derived from the cellular metabolism. Volatile organic compounds can be analyzed to identify the individual chemical elements as well as their pattern of expression to reproduce a sensorial combination similar to a fingerprint (breathprint). The e-nose can be used alone, mimicking the combinatorial selectivity of the human olfactory system, or as part of a multisensorial platform. This review analyzes the progress made by investigators interested in this technology as well as the perspectives for its future utilization.

Asthma Endotypes and an Overview of Targeted Therapy for Asthma

Guidelines for the management of severe asthma do not emphasize the measurement of the inflammatory component of airway disease to indicate appropriate treatments or to monitor response to treatment. Inflammation is a central component of asthma and contributes to symptoms, physiological, and structural abnormalities. It can be assessed by a number of endotyping strategies based on “omics” technology such as proteomics, transcriptomics, and metabolomics. It can also be assessed using simple cellular responses by quantitative cytometry in sputum. Bronchitis may be eosinophilic, neutrophilic, mixed-granulocytic, or paucigranulocytic (eosinophils and neutrophils not elevated). Eosinophilic bronchitis is usually a Type 2 (T2)-driven process and therefore a sputum eosinophilia of greater than 3% usually indicates a response to treatment with corticosteroids or novel therapies directed against T2 cytokines such as IL-4, IL-5, and IL-13. Neutrophilic bronchitis represents a non-T2-driven disease, which is generally a predictor of response to antibiotics and may be a predictor to therapies targeted at pathways that lead to neutrophil recruitment such as TNF, IL-1, IL-6, IL-8, IL-23, and IL-17. Paucigranulocytic disease may not warrant anti-inflammatory therapy. These patients, whose symptoms may be driven largely by airway hyper-responsiveness may benefit from smooth muscle-directed therapies such as bronchial thermoplasty or mast-cell directed therapies. This review will briefly summarize the current knowledge regarding “omics-based signatures” and cellular endotyping of severe asthma and give an overview of segmentation of asthma therapeutics guided by the endotype.

Predictive Biomarkers for Asthma Therapy

PURPOSE OF REVIEW

Asthma is a heterogeneous disease characterized by multiple phenotypes. Treatment of patients with severe disease can be challenging. Predictive biomarkers are measurable characteristics that reflect the underlying pathophysiology of asthma and can identify patients that are likely to respond to a given therapy. This review discusses current knowledge regarding predictive biomarkers in asthma.

RECENT FINDINGS

Recent trials evaluating biologic therapies targeting IgE, IL-5, IL-13, and IL-4 have utilized predictive biomarkers to identify patients who might benefit from treatment. Other work has suggested that using composite biomarkers may offer enhanced predictive capabilities in tailoring asthma therapy. Multiple biomarkers including sputum eosinophil count, blood eosinophil count, fractional concentration of nitric oxide in exhaled breath (FeNO), and serum periostin have been used to identify which patients will respond to targeted asthma medications. Further work is needed to integrate predictive biomarkers into clinical practice.

Development of Diamond and Silicon MEMS Sensor Arrays with Integrated Readout for Vapor Detection

This paper reports on the development of an autonomous instrument based on an array of eight resonant microcantilevers for vapor detection. The fabricated sensors are label-free devices, allowing chemical and biological functionalization. In this work, sensors based on an array of silicon and synthetic diamond microcantilevers are sensitized with polymeric films for the detection of analytes. The main advantage of the proposed system is that sensors can be easily changed for another application or for cleaning since the developed gas cell presents removable electrical connections. We report the successful application of our electronic nose approach to detect 12 volatile organic compounds. Moreover, the response pattern of the cantilever arrays is interpreted via principal component analysis (PCA) techniques in order to identify samples.

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.

Significance of Exhaled Breath Test in Clinical Diagnosis: A Special Focus on the Detection of Diabetes Mellitus

Analysis of volatile organic compounds (VOCs) emanating from human exhaled breath can provide deep insight into the status of various biochemical processes in the human body. VOCs can serve as potential biomarkers of physiological and pathophysiological conditions related to several diseases. Breath VOC analysis, a noninvasive and quick biomonitoring approach, also has potential for the early detection and progress monitoring of several diseases. This paper gives an overview of the major VOCs present in human exhaled breath, possible biochemical pathways of breath VOC generation, diagnostic importance of their analysis, and analytical techniques used in the breath test. Breath analysis relating to diabetes mellitus and its characteristic breath biomarkers is focused on. Finally, some challenges and limitations of the breath test are discussed.

Feasibility of electronic nose technology for discriminating between head and neck, bladder, and colon carcinomas

Electronic nose (e-nose) technology has the potential to detect cancer at an early stage and can differentiate between cancer origins. Our objective was to compare patients who had head and neck squamous cell carcinoma (HNSCC) with patients who had colon or bladder cancer to determine the distinctive diagnostic characteristics of the e-nose. Feasibility study An e-nose device was used to collect samples of exhaled breath from patients who had HNSCC and those who had bladder or colon cancer, after which the samples were analyzed and compared. One hundred patients with HNSCC, 40 patients with bladder cancer, and 28 patients with colon cancer exhaled through an e-nose for 5 min. An artificial neural network was used for the analysis, and double cross-validation to validate the model. In differentiating HNSCC from colon cancer, a diagnostic accuracy of 81 % was found. When comparing HNSCC with bladder cancer, the diagnostic accuracy was 84 %. A diagnostic accuracy of 84 % was found between bladder cancer and colon cancer. The e-nose technique using double cross-validation is able to discriminate between HNSCC and colon cancer and between HNSCC and bladder cancer. Furthermore, the e-nose technique can distinguish colon cancer from bladder cancer.

Breathomics in the setting of asthma and chronic obstructive pulmonary disease

Exhaled breath contains thousands of volatile organic compounds that reflect the metabolic process occurring in the host both locally in the airways and systemically. They also arise from the environment and airway microbiome. Comprehensive analysis of breath volatile organic compounds (breathomics) provides opportunities for noninvasive biomarker discovery and novel mechanistic insights. Applications in patients with obstructive lung diseases, such as asthma and chronic obstructive pulmonary disease, include not only diagnostics (especially in children and other challenging diagnostic areas) but also identification of clinical treatable traits, such as airway eosinophilia and risk of infection/exacerbation, that are not specific to diagnostic labels. Although many aspects of breath sampling and analysis are challenging, proof-of-concept studies with mass spectrometry and electronic nose technologies have provided independent studies with moderate-to-good diagnostic and phenotypic accuracies. The present review evaluates the data obtained by using breathomics in (1) predicting the inception of asthma or chronic obstructive pulmonary disease, (2) inflammatory phenotyping, (3) exacerbation prediction, and (4) treatment stratification. The current findings merit the current efforts of large multicenter studies using standardized sampling, shared analytic methods, and databases, including external validation cohorts. This will position this noninvasive technology in the clinical assessment and monitoring of chronic airways diseases.

Identification of a Large Pool of Microorganisms with an Array of Porphyrin Based Gas Sensors

The association between volatile compounds (VCs) and microorganisms, as demonstrated by several studies, may offer the ground for a rapid identification of pathogens. To this regard, chemical sensors are a key enabling technology for the exploitation of this opportunity. In this study, we investigated the performance of an array of porphyrin-coated quartz microbalance gas sensors in the identification of a panel of 12 bacteria and fungi. The porphyrins were metal complexes and the free base of a functionalized tetraphenylporphyrin. Our results show that the sensor array distinguishes the VC patterns produced by microorganisms in vitro. Besides being individually identified, bacteria are also sorted into Gram-positive and Gram-negative.

Exhaled Breath Analysis for Monitoring Response to Treatment in Advanced Lung Cancer

INTRODUCTION

The Response Evaluation Criteria in Solid Tumors (RECIST) serve as the accepted standard to monitor treatment efficacy in lung cancer. However, the time intervals between consecutive computerized tomography scans might be too long to allow early identification of treatment failure. This study examines the use of breath sampling to monitor responses to anticancer treatments in patients with advanced lung cancer.

METHODS

A total of 143 breath samples were collected from 39 patients with advanced lung cancer. The exhaled breath signature, determined by gas chromatography/mass spectrometry and a nanomaterial-based array of sensors, was correlated with the response to therapy assessed by RECIST: complete response, partial response, stable disease, or progressive disease.

RESULTS

Gas chromatography/mass spectrometry analysis identified three volatile organic compounds as significantly indicating disease control (PR/stable disease), with one of them also significantly discriminating PR/stable disease from progressive disease. The nanoarray had the ability to monitor changes in tumor response across therapy, also indicating any lack of further response to therapy. When one-sensor analysis was used, 59% of the follow-up samples were identified correctly. There was 85% success in monitoring disease control (stable disease/partial response).

CONCLUSION

Breath analysis, using mainly the nanoarray, may serve as a surrogate marker for the response to systemic therapy in lung cancer. As a monitoring tool, it can provide the oncologist with a quick bedside method of identifying a lack of response to an anticancer treatment. This may allow quicker recognition than does the current RECIST analysis. Early recognition of treatment failure could improve patient care.

Volatile organic compounds in asthma diagnosis: a systematic review and meta-analysis

We aimed to assess the value and classification rate of exhaled volatile organic compounds (VOCs) in asthma diagnosis. A PRISMA-oriented systematic search for published studies regarding exhaled VOCs in asthma diagnosis was conducted based on predefined criteria. Studies presenting sensitivity and specificity values for the test were included in the meta-analysis. Pooled diagnosis odds ratios (DOR), area under the curve (AUC) and positive and negative likelihood ratios (LR) for exhaled VOC profiles were calculated; and publication bias, threshold effect and heterogeneity were estimated. Eighteen studies were selected for the qualitative analysis and six met the criteria for inclusion in the quantitative analysis. Mean (95% CI) pooled DOR, positive and negative LR were 49.3 (15.9-153.3), 5.86 (3.07-11.21) and 0.16 (0.10-0.26), respectively. The AUC value was 0.94. Only three of the 18 reviewed studies performed an external validation of the model using a different data set. The results from the revised studies suggest that exhaled VOCs are promising biomarkers for asthma diagnosis and that several compounds, mainly alkanes, may be significantly associated with asthma inflammation. However, there are still various constraints associated with standardization and externally validated studies are needed to introduce exhaled VOC profiling in a clinical scenario.

Nanoscale Sensor Technologies for Disease Detection via Volatolomics

The detection of many diseases is missed because of delayed diagnoses or the low efficacy of some treatments. This emphasizes the urgent need for inexpensive and minimally invasive technologies that would allow efficient early detection, stratifying the population for personalized therapy, and improving the efficacy of rapid bed-side assessment of treatment. An emerging approach that has a high potential to fulfill these needs is based on so-called "volatolomics", namely, chemical processes involving profiles of highly volatile organic compounds (VOCs) emitted from body fluids, including breath, skin, urine and blood. This article presents a didactic review of some of the main advances related to the use of nanomaterial-based solid-state and flexible sensors, and related artificially intelligent sensing arrays for the detection and monitoring of disease with volatolomics. The article attempts to review the technological gaps and confounding factors related to VOC testing. Different ways to choose nanomaterial-based sensors are discussed, while considering the profiles of targeted volatile markers and possible limitations of applying the sensing approach. Perspectives for taking volatolomics to a new level in the field of diagnostics are highlighted.

Integration of electronic nose technology with spirometry: validation of a new approach for exhaled breath analysis

New 'omics'-technologies have the potential to better define airway disease in terms of pathophysiological and clinical phenotyping. The integration of electronic nose (eNose) technology with existing diagnostic tests, such as routine spirometry, can bring this technology to 'point-of-care'. We aimed to determine and optimize the technical performance and diagnostic accuracy of exhaled breath analysis linked to routine spirometry. Exhaled breath was collected in triplicate in healthy subjects by an eNose (SpiroNose) based on five identical metal oxide semiconductor sensor arrays (three arrays monitoring exhaled breath and two reference arrays monitoring ambient air) at the rear end of a pneumotachograph. First, the influence of flow, volume, humidity, temperature, environment, etc, was assessed. Secondly, a two-centre case-control study was performed using diagnostic and monitoring visits in day-to-day clinical care in patients with a (differential) diagnosis of asthma, chronic obstructive pulmonary disease (COPD) or lung cancer. Breathprint analysis involved signal processing, environment correction based on alveolar gradients and statistics based on principal component (PC) analysis, followed by discriminant analysis (Matlab2014/SPSS20). Expiratory flow showed a significant linear correlation with raw sensor deflections (R(2)  =  0.84) in 60 healthy subjects (age 43  ±  11 years). No correlation was found between sensor readings and exhaled volume, humidity and temperature. Exhaled data after environment correction were highly reproducible for each sensor array (Cohen's Kappa 0.81-0.94). Thirty-seven asthmatics (41  ±  14.2 years), 31 COPD patients (66  ±  8.4 years), 31 lung cancer patients (63  ±  10.8 years) and 45 healthy controls (41  ±  12.5 years) entered the cross-sectional study. SpiroNose could adequately distinguish between controls, asthma, COPD and lung cancer patients with cross-validation values ranging between 78-88%. We have developed a standardized way to integrate eNose technology with spirometry. Signal processing techniques and environmental background correction ensured that the multiple sensor arrays within the SpiroNose provided repeatable and interchangeable results. SpiroNose discriminated controls and patients with asthma, COPD and lung cancer with promising accuracy, paving the route towards point-of-care exhaled breath diagnostics.

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.

Breathomics in lung disease

Volatile organic compounds (VOCs) are produced by virtually all metabolic processes of the body. As such, they have potential to serve as noninvasive metabolic biomarkers. Since exhaled VOCs are either derived from the respiratory tract itself or have passed the lungs from the circulation, they are candidate biomarkers in the diagnosis and monitoring of pulmonary diseases in particular. Good examples of the possibilities of exhaled volatiles in pulmonary medicine are provided by the potential use of VOCs to discriminate between patients with lung cancer and healthy control subjects and to noninvasively diagnose infectious diseases and the association between VOCs and markers of disease activity that has been established in obstructive lung diseases. Several steps are, however, required prior to implementation of breath-based diagnostics in daily clinical practice. First, VOCs should be studied in the intention-to-diagnose population, because biomarkers are likely to be affected by multiple (comorbid) conditions. Second, breath collection and analysis procedures need to be standardized to allow pooling of data. Finally, apart from probabilistic analysis for diagnostic purposes, detailed examination of the nature of volatile biomarkers not only will improve our understanding of the pathophysiologic origins of these markers and the nature of potential confounders but also can enable the development of sensors that exhibit maximum sensitivity and specificity toward specific applications. By adhering to such an approach, exhaled biomarkers can be validated in the diagnosis, monitoring, and treatment of patients in pulmonary medicine and contribute to the development of personalized medicine.

Advances in electronic-nose technologies for the detection of volatile biomarker metabolites in the human breath

Recent advancements in the use of electronic-nose (e-nose) devices to analyze human breath profiles for the presence of specific volatile metabolites, known as biomarkers or chemical bio-indicators of specific human diseases, metabolic disorders and the overall health status of individuals, are providing the potential for new noninvasive tools and techniques useful to point-of-care clinical disease diagnoses. This exciting new area of electronic disease detection and diagnosis promises to yield much faster and earlier detection of human diseases and disorders, allowing earlier, more effective treatments, resulting in more rapid patient recovery from various afflictions. E-nose devices are particularly suited for the field of disease diagnostics, because they are sensitive to a wide range of volatile organic compounds (VOCs) and can effectively distinguish between different complex gaseous mixtures via analysis of electronic aroma sensor-array output profiles of volatile metabolites present in the human breath. This review provides a summary of some recent developments of electronic-nose technologies, particularly involving breath analysis, with the potential for providing many new diagnostic applications for the detection of specific human diseases associated with different organs in the body, detectable from e-nose analyses of aberrant disease-associated VOCs present in air expired from the lungs.

Breath analysis as a potential and non-invasive frontier in disease diagnosis: an overview

Currently, a small number of diseases, particularly cardiovascular (CVDs), oncologic (ODs), neurodegenerative (NDDs), chronic respiratory diseases, as well as diabetes, form a severe burden to most of the countries worldwide. Hence, there is an urgent need for development of efficient diagnostic tools, particularly those enabling reliable detection of diseases, at their early stages, preferably using non-invasive approaches. Breath analysis is a non-invasive approach relying only on the characterisation of volatile composition of the exhaled breath (EB) that in turn reflects the volatile composition of the bloodstream and airways and therefore the status and condition of the whole organism metabolism. Advanced sampling procedures (solid-phase and needle traps microextraction) coupled with modern analytical technologies (proton transfer reaction mass spectrometry, selected ion flow tube mass spectrometry, ion mobility spectrometry, e-noses, etc.) allow the characterisation of EB composition to an unprecedented level. However, a key challenge in EB analysis is the proper statistical analysis and interpretation of the large and heterogeneous datasets obtained from EB research. There is no standard statistical framework/protocol yet available in literature that can be used for EB data analysis towards discovery of biomarkers for use in a typical clinical setup. Nevertheless, EB analysis has immense potential towards development of biomarkers for the early disease diagnosis of diseases.

Novel biomarkers for asthma stratification and personalized therapy

A stepwise pharmacological treatment is currently recommended for all asthma patients and is personalized mainly on disease severity, aiming for the lowest disease-controlling step. Nevertheless, asthma comprises several related pathologies with similar clinical manifestations resulting from distinct underlying mechanisms. Therefore novel biomarkers could lead to asthma stratification and thus improve upon the current stepwise approach. The aim of this review is to update the reader with regard to different assays proposed in the recent asthma literature for measuring potential biomarkers for patient stratification and treatment personalization. Promising biomarkers are sputum eosinophils, serum periostin and exhaled nitric oxide. Periostin could differentiate between Th2-high and Th2-low asthma (Th2-high patients are more responsive to glucocorticoids) and the less-defined asthma types which often present a therapeutic challenge. Several other biomarkers, mainly cytokines, leukotrienes and exhaled air components, can be quantified in body fluids and exhaled breath and could also be useful for asthma stratification.

Predicting steroid responsiveness in patients with asthma using exhaled breath profiling

BACKGROUND

Exhaled breath contains disease-dependent volatile organic compounds (VOCs), which may serve as biomarkers distinguishing clinical phenotypes in asthma. Their measurement may be particularly beneficial in relation to treatment response.

OBJECTIVE

Our aim was to compare the performance of electronic nose (eNose) breath analysis with previously investigated techniques (sputum eosinophils, exhaled nitric oxide (FeNO) and airway hyperresponsiveness) to discriminate asthma from controls and identify steroid responsiveness in steroid-free patients. Trial registration ACTRN12613000038796.

METHODS

Twenty-five patients with mild/moderate asthma had their inhaled steroid treatment discontinued until loss of control or 28 days. They were subsequently treated with oral prednisone 30 mg/day for 14 days. Steroid responsiveness was defined as an increase of either > 12% FEV1 or > 2 doubling doses PC20 AMP. Steroid-free assessment of sputum eosinophils, FeNO and exhaled breath VOCs were used to construct algorithms predicting steroid responsiveness. Performance characteristics were compared by ROC analysis.

RESULTS

The eNose discriminated between asthma and controls (area under the curve = 0.766 ± 0.14; P = 0.002) with similar accuracy to FeNO (0.862 ± 0.12; P < 0.001) and sputum eosinophils (0.814 ± 0.15; P < 0.001). Steroid responsiveness was predicted with greater accuracy by VOC-analysis (AUC = 0.883 ± 0.16; P = 0.008) than FeNO (0.545 ± 0.28; P = 0.751) or sputum eosinophils (0.610 ± 0.29; P = 0.441).

CONCLUSIONS AND CLINICAL RELEVANCE

Breath analysis by eNose can identify asthmatic patients and may be used to predict their response to steroids with greater accuracy than sputum eosinophils or FeNO. This implies a potential role for breath analysis in the tailoring of treatment for asthma patients.

Review article: next generation diagnostic modalities in gastroenterology--gas phase volatile compound biomarker detection

BACKGROUND

The detection of airborne gas phase biomarkers that emanate from biological samples like urine, breath and faeces may herald a new age of non-invasive diagnostics. These biomarkers may reflect status in health and disease and can be detected by humans and other animals, to some extent, but far more consistently with instruments. The continued advancement in micro and nanotechnology has produced a range of compact and sophisticated gas analysis sensors and sensor systems, focussed primarily towards environmental and security applications. These instruments are now increasingly adapted for use in clinical testing and with the discovery of new gas volatile compound biomarkers, lead naturally to a new era of non-invasive diagnostics.

AIM

To review current sensor instruments like the electronic nose (e-nose) and ion mobility spectroscopy (IMS), existing technology like gas chromatography-mass spectroscopy (GC-MS) and their application in the detection of gas phase volatile compound biomarkers in medicine - focussing on gastroenterology.

METHODS

A systematic search on Medline and Pubmed databases was performed to identify articles relevant to gas and volatile organic compounds.

RESULTS

E-nose and IMS instruments achieve sensitivities and specificities ranging from 75 to 92% in differentiating between inflammatory bowel disease, bile acid diarrhoea and colon cancer from controls. For pulmonary disease, the sensitivities and specificities exceed 90% in differentiating between pulmonary malignancy, pneumonia and obstructive airways disease. These sensitivity levels also hold true for diabetes (92%) and bladder cancer (90%) when GC-MS is combined with an e-nose.

CONCLUSIONS

The accurate reproducible sensing of volatile organic compounds (VOCs) using portable near-patient devices is a goal within reach for today's clinicians.

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.

Analysis of Airborne Biomarkers for Point-of-Care Diagnostics

Treatable diseases continue to exact a heavy burden worldwide despite powerful advances in treatment. Diagnostics play crucial roles in the detection, management, and ultimate prevention of these diseases by guiding the allocation of precious medical resources. Motivated by globalization and evolving disease, and enabled by advances in molecular pathology, the scientific community has produced an explosion of research on miniaturized integrated biosensor platforms for disease detection. Low-cost, automated tests promise accessibility in low-resource settings by loosening constraints around infrastructure and usability. To address the challenges raised by invasive and intrusive sample collection, researchers are exploring alternative biomarkers in various specimens. Specifically, patient-generated airborne biomarkers suit minimally invasive collection and automated analysis. Disease biomarkers are known to exist in aerosols and volatile compounds in breath, odor, and headspace, media that can be exploited for field-ready diagnostics. This article reviews global disease priorities and the characteristics of low-resource settings. It surveys existing technologies for the analysis of bioaerosols and volatile organic compounds, and emerging technologies that could enable their translation to the point of care. Engineering advances promise to enable appropriate diagnostics by detecting chemical and microbial markers. Nonetheless, further innovation and cost reduction are needed for these technologies to broadly affect global health.

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.

Nanomaterial-based sensors for detection of disease by volatile organic compounds

The importance of developing new diagnostic and detection technologies for the growing number of clinical challenges is rising each year. Here, we present a concise, yet didactic review on a new diagnostics frontier based on the detection of disease-related volatile organic compounds (VOCs) by means of nanomaterial-based sensors. Nanomaterials are ideal for such sensor arrays because they are easily fabricated, chemically versatile and can be integrated into currently available sensing platforms. Following a general introduction, we provide a brief description of the VOC-related diseases concept. Then, we focus on detection of VOC-related diseases by selective and crossreactive sensing approaches, through chemical, optical and mechanical transducers incorporating the most important classes of nanomaterials. Selected examples of the integration of nanomaterials into selective sensors and crossreactive sensor arrays are given. We conclude with a brief discussion on the integration possibilities of different types of nanomaterials into sensor arrays, and the expected outcomes and limitations.

Application of an electronic nose in the diagnosis of head and neck cancer

OBJECTIVES/HYPOTHESIS

Electronic nose (E-nose) technology has various applications such as the monitoring of air quality and the detection of explosive and chemical agents. We studied the diagnostic accuracy of volatile organic compounds (VOC) pattern analysis in exhaled breath by means of an E-nose in patients with head and neck squamous cell carcinoma (HNSCC).

STUDY DESIGN

Cohort study. Exhaled breath samples from patients with HNSCC were analyzed by using an E-Nose.

METHODS

Thirty-six patients diagnosed with HNSCC exhaled into a 5-litre Tedlar bag. The control group consisted of 23 patients visiting the outpatient clinic for other (benign) conditions. Air samples were analyzed using an E-nose.

RESULTS

Logistic regression showed a significant difference (P < 0.05) in VOC resistance patterns between patients diagnosed with HNSCC and the control group, with a sensitivity of 90% and a corresponding specificity of 80%.

CONCLUSIONS

E-nose application holds a promising potential for application in the diagnosis of HNSCC due to its rapid, simple, and noninvasive nature.

LEVEL OF EVIDENCE

3b.

Detection of volatile organic compounds as biomarkers in breath analysis by different analytical techniques

Breath is a rich mixture containing numerous volatile organic compounds at trace amounts (ppbv–pptv level) such as: hydrocarbons, alcohols, ketones, aldehydes, esters or heterocycles. The presence of some of them depends on health status. Therefore, breath analysis might be useful for clinical diagnostics, therapy monitoring and control of metabolic or biochemical cell cycle products. This Review presents an update on the latest developments in breath analysis applied to diagnosing different diseases with the help of high-quality equipment. Efforts were made to fully and accurately describe traditional and modern techniques used to determine the components of breath. The techniques were compared in terms of design, function and also detection limit of different volatile organic compounds. GC with different detectors, MS, optical sensor and laser spectroscopic detection techniques are also discussed.

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.

Detection and identification of cancers by the electronic nose

INTRODUCTION

The early determination of serious pathologies has so far been an important issue in both the medical and social fields. The search for an instrument able to detect cancers has led to the consideration of the usage of chemicals of the human body, which carry, through its volatile compounds, information coming from or related to defined pathologies.

AREAS COVERED

The electronic nose (EN) seems to represent a good solution for the detection of cancers of different types. Recent results showed the utility of an EN to smell chemicals related to lung, melanoma, prostatic, breast and pancreatic cancers. The results obtainable from ENs are chemical images and, as it will be shown in this paper, the probability of cancer recognition is rather high. Main results obtained at international level and by the authors of this paper will be commented upon.

EXPERT OPINION

A personal opinion is given trying to foresee future developments of the olfaction strategy. To this purpose, two main aspects are considered: looking for better overall stability of the EN and for a new use of ENs in detecting alterations between blood and pathology components.

A mobile instrumentation platform to distinguish airway disorders

Asthma and chronic obstructive pulmonary disease (COPD) are distinct but clinically overlapping airway disorders which often create diagnostic and therapeutic dilemmas. Current strategies to discriminate these diseases are limited by insensitivity and poor performance due to biologic variability. We tested the hypothesis that a gas chromatograph/differential mobility spectrometer (GC/DMS) sensor could distinguish between clinically well-defined groups with airway disorders based on the volatile organic compounds (VOCs) obtained from exhaled breath. After comparing VOC profiles obtained from 13 asthma, 5 COPD and 13 healthy control subjects, we found that VOC profiles distinguished asthma from healthy controls and also a subgroup of asthmatics taking the drug omalizumab from healthy controls. The VOC profiles could not distinguish between COPD and any of the other groups. Our results show a potential application of the GC/DMS for non-invasive and bedside diagnostics of asthma and asthma therapy monitoring. Future studies will focus on larger sample sizes and patient cohorts.

Effect of transportation and storage using sorbent tubes of exhaled breath samples on diagnostic accuracy of electronic nose analysis

Many (multi-centre) breath-analysis studies require transport and storage of samples. We aimed to test the effect of transportation and storage using sorbent tubes of exhaled breath samples for diagnostic accuracy of eNose and GC-MS analysis. As a reference standard for diagnostic accuracy, breath samples of asthmatic patients and healthy controls were analysed by three eNose devices. Samples were analysed by GC-MS and eNose after 1, 7 and 14 days of transportation and storage using sorbent tubes. The diagnostic accuracy for eNose and GC-MS after storage was compared to the reference standard. As a validation, the stability was assessed of 15 compounds known to be related to asthma, abundant in breath or related to sampling and analysis. The reference test discriminated asthma and healthy controls with a median AUC (range) of 0.77 (0.72-0.76). Similar accuracies were achieved at t1 (AUC eNose 0.78; GC-MS 0.84), t7 (AUC eNose 0.76; GC-MS 0.79) and t14 (AUC eNose 0.83; GC-MS 0.84). The GC-MS analysis of compounds showed an adequate stability for all 15 compounds during the 14 day period. Short-term transportation and storage using sorbent tubes of breath samples does not influence the diagnostic accuracy for discrimination between asthma and health by eNose and GC-MS.

Clinical use of exhaled volatile organic compounds in pulmonary diseases: a systematic review

There is an increasing interest in the potential of exhaled biomarkers, such as volatile organic compounds (VOCs), to improve accurate diagnoses and management decisions in pulmonary diseases. The objective of this manuscript is to systematically review the current knowledge on exhaled VOCs with respect to their potential clinical use in asthma, lung cancer, chronic obstructive pulmonary disease (COPD), cystic fibrosis (CF), and respiratory tract infections. A systematic literature search was performed in PubMed, EMBASE, Cochrane database, and reference lists of retrieved studies. Controlled, clinical, English-language studies exploring the diagnostic and monitoring value of VOCs in asthma, COPD, CF, lung cancer and respiratory tract infections were included. Data on study design, setting, participant characteristics, VOCs techniques, and outcome measures were extracted. Seventy-three studies were included, counting in total 3,952 patients and 2,973 healthy controls. The collection and analysis of exhaled VOCs is non-invasive and could be easily applied in the broad range of patients, including subjects with severe disease and children. Various research groups demonstrated that VOCs profiles could accurately distinguish patients with a pulmonary disease from healthy controls. Pulmonary diseases seem to be characterized by a disease specific breath-print, as distinct profiles were found in patients with dissimilar diseases. The heterogeneity of studies challenged the inter-laboratory comparability. In conclusion, profiles of VOCs are potentially able to accurately diagnose various pulmonary diseases. Despite these promising findings, multiple challenges such as further standardization and validation of the diverse techniques need to be mastered before VOCs can be applied into clinical practice.

Bronchial and alveolar nitric oxide in exercise-induced bronchoconstriction in asthmatic children

BACKGROUND

Epidemiological studies have shown an association between the severity of exercise-induced bronchoconstriction (EIB) and fractional exhaled nitric oxide at the flow of 50 mL/s (FeNO(50)). However, no study has assessed the correlation between alveolar production (C(alv)) and bronchial flux (J(NO)) of nitric oxide (NO) and EIB in asthmatic children.

OBJECTIVE

To identify the relationship between severity of EIB and bronchial or alveolar nitric oxide.

METHODS

Our group included 36 allergic children with intermittent asthma. The EIB was determined by a standard exercise challenge and the severity was expressed as the maximum change in percentage from the baseline value of lung function (ΔFEV(1)%, ΔFEF(25-75)%) after exercising. A chemiluminescence analyser at multiple flows was used to calculate FeNO(50), J(NO) and C(alv,) which reflect large airways, J(NO) and alveolar concentration of NO respectively.

RESULTS

Sixteen (44.4%) children presented a ∆FEV(1) ≥ 10%, eight (22.2%) had ∆FEV(1) ≥ 15% and nine (25%) children had a ∆FEF(25-75) ≥ 26%. A significant correlation was observed between severity of EIB and FeNO(50) , J(NO) and C(alv.) EIB was significantly more severe in children sensitive to indoor allergens compared with outdoor allergens only (P = 0.014); those children showed also higher levels of C(alv) (P = 0.003) and of J(NO) (P = 0.044).

CONCLUSIONS AND CLINICAL RELEVANCE

Our results suggest that inflammation is present in the central and peripheral airways and that it is associated with the severity of EIB. Clinicaltrials.gov NCT00952835.

Reproducibility and respiratory function correlates of exhaled breath fingerprint in chronic obstructive pulmonary disease

BACKGROUND

The electronic nose (e nose) provides distinctive breath fingerprints for selected respiratory diseases. Both reproducibility and respiratory function correlates of breath fingerprint are poorly known.

OBJECTIVES

To measure reproducibility of breath fingerprints and to assess their correlates among respiratory function indexes in elderly healthy and COPD subjects.

METHOD

25 subjects (5 COPD patients for each GOLD stage and 5 healthy controls) over 65 years underwent e-nose study through a seven sensor system and respiratory function tests at times 0, 7, and 15 days. Reproducibility of the e nose pattern was computed. The correlation between volatile organic compound (VOC) pattern and respiratory function/clinical parameters was assessed by the Spearman's rho.

MEASUREMENTS AND MAIN RESULTS

VOC patterns were highly reproducible within healthy and GOLD 4 COPD subjects, less among GOLD 1-3 patients.VOC patterns significantly correlated with expiratory flows (Spearman's rho ranging from 0.36 for MEF25% and sensor Co-Buti-TPP, to 0.81 for FEV1% and sensor Cu-Buti-TPP p<0.001)), but not with residual volume and total lung capacity.

CONCLUSIONS

VOC patterns strictly correlated with expiratory flows. Thus, e nose might conveniently be used to assess COPD severity and, likely, to study phenotypic variability. However, the suboptimal reproducibility within GOLD 1-3 patients should stimulate further research to identify more reproducible breath print patterns.

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.

Long-Term Adjustment of Stable Asthma Treatment with Fractional Exhaled Nitric Oxide and Sputum Eosinophils

Current approaches to control asthma do not involve direct assessment of airway inflammation. The aim of this study is to assess whether the therapeutic adjustments of steroid treatment according to a stepwise algorithm based on sputum Eosinophils (sEos) and fractioned exhaled Nitric Oxide (FeNO) were effective in maintaining the stability of a group of stable asthmatic patients during a twelvemonth follow-up. Fourteen asthmatic patients, treated for asthma according to a previously published protocol, were enrolled in the study. The patients underwent clinical evaluation, pulmonary function tests, measuring of airway hyperresponsiveness to methacholine, and determination of FeNO and sEos at visit 1. These procedures were repeated after 6 and 12 months (Visits 2 and 3, respectively). Symptoms score gradually improved during the study (p=0.008), no changes were observed in the frequency of clinical asthma exacerbations or in airway hyperresponsiveness to methacholine. At the end of the study both sEos and FeNO were significantly improved (p=0.011 and p=0.003, respectively) and at visit 3 the median steroid dose was reduced (p=0.039) in accordance with the improving of symptoms score, FeNO and sEos values. A direct relationship was observed between the difference of FeNO values and the difference of sEos registered between visits 1 and 2 (r2=609, p0.001) and between visits 2 and 3 (r2=646, p<0.001). In conclusion, long-term titration of asthma inhaled steroid treatment based on sEos and FeNO values was able to provide long-term clinical stability and improvement to the asthmatic patients studied, without significant increases in the steroid dose.