Breath biomarkers of active pulmonary tuberculosis

Sensors for detecting pulmonary diseases from exhaled breath

This review presents and discusses a new frontier for fast, risk-free and potentially inexpensive diagnostics of respiratory diseases by detecting volatile organic compounds (VOCs) present in exhaled breath. One part of the review is a didactic presentation of the overlaying concept and the chemistry of exhaled breath. The other part discusses diverse sensors that have been developed and used for the detection of respiratory diseases (e.g. chronic obstructive pulmonary disease, asthma, lung cancer, pulmonary arterial hypertension, tuberculosis, cystic fibrosis, obstructive sleep apnoea syndrome and pneumoconiosis) by analysis of VOCs in exhaled breath. The strengths and pitfalls are discussed and criticised, particularly in the perspective in disseminating information regarding these advances. Ideas regarding the improvement of sensors, sensor arrays, sensing devices and the further planning of workflow are also discussed.

Detection of volatile organic compounds from exhaled breath by nanomaterial-based sensors is a new diagnostics frontier in the screening of pulmonary diseases.http://bit.ly/2JoBKXn

Examining the Complex Relationship Between Tuberculosis and Other Infectious Diseases in Children

Millions of children are exposed to tuberculosis (TB) each year, many of which become infected with Mycobacterium tuberculosis. Most children can immunologically contain or eradicate the organism without pathology developing. However, in a minority, the organism overcomes the immunological constraints, proliferates and causes TB disease. Each year a million children develop TB disease, with a quarter dying. While it is known that young children and those with immunodeficiencies are at increased risk of progression from TB infection to TB disease, our understanding of risk factors for this transition is limited. The most immunologically disruptive process that can happen during childhood is infection with another pathogen and yet the impact of co-infections on TB risk is poorly investigated. Many diseases have overlapping geographical distributions to TB and affect similar patient populations. It is therefore likely that infection with viruses, bacteria, fungi and protozoa may impact on the risk of developing TB disease following exposure and infection, although disentangling correlation and causation is challenging. As vaccinations also disrupt immunological pathways, these may also impact on TB risk. In this article we describe the pediatric immune response to M. tuberculosis and then review the existing evidence of the impact of co-infection with other pathogens, as well as vaccination, on the host response to M. tuberculosis. We focus on the impact of other organisms on the risk of TB disease in children, in particularly evaluating if co-infections drive host immune responses in an age-dependent way. We finally propose priorities for future research in this field. An improved understanding of the impact of co-infections on TB could assist in TB control strategies, vaccine development (for TB vaccines or vaccines for other organisms), TB treatment approaches and TB diagnostics.

Modeling cellular metabolomic effects of oxidative stress impacts from hydrogen peroxide and cigarette smoke on human lung epithelial cells

The respiratory system is continuously exposed to variety of biological and chemical irritants that contain reactive oxygen species, and these are well known to cause oxidative stress responses in lung epithelial cells. There is a clinical need to identify biomarkers of oxidative stress which could potentially support early indicators of disease and health management. To identify volatile biomarkers of oxidative stress, we analyzed the headspace above human bronchial epithelial cell cultures (HBE1) before and after hydrogen peroxide (H₂O₂) and cigarette smoke extract (CSE) exposure. Using stir bar and headspace sorptive extraction-gas chromatography-mass spectrometry, we searched for volatile organic compounds (VOC) of these oxidative measures. In the H₂O₂ cell peroxidation experiments, four different H₂O₂ concentrations (0.1, 0.5, 10, 50 mM) were applied to the HBE1 cells, and VOCs were collected every 12 h over the time course of 48 h. In the CSE cell peroxidation experiments, four different smoke extract concentrations (0%, 10%, 30%, 60%) were applied to the cells, and VOCs were collected every 12 h over the time course of 48 h. We used partial-least squares (PLS) analysis to identify putative compounds from the mass spectrometry results that highly correlated with the known applied oxidative stress. We observed chemical emissions from the cells that related to both the intensity of the oxidative stress and followed distinct time courses. Additionally, some of these chemicals are aldehydes, which are thought to be non-invasive indicators of oxidative stress in exhaled human breath. Together, these results illustrate a powerful in situ cell culture model of oxidative stress that can be used to explore the putative biological genesis of exhaled breath biomarkers that are often observed in human clinical studies.

Newer Diagnostic Tests and their Application in Pediatric TB

The diagnosis of childhood tuberculosis is a challenge due to the pauci-bacillary nature of infection and the difficulty in obtaining appropriate sample. In the past 2-3 decades, many new tests were introduced for the diagnosis of tuberculosis (TB) and some of them have been evaluated for their application in pediatric tuberculosis as well. There is an attempt to improve smear microscopy by introducing light-emitting diode (LED) fluorescence microscopy and there are also some automated digital microscopy platforms under evaluation. Introduction of automated liquid culture platform along with rapid molecular based identification methods have considerably reduced the time delay in mycobacterial culture. Recent addition of many nucleic acid amplification platforms like Amplicor PCR, Genprobe, Xpert MTB/Rif, line probe assays, loop mediated isothermal amplification etc are also been found to be useful. Latest techniques like microarray and gene sequencing are also being used in clinical laboratories with variable results. Indirect methods of TB diagnosis like T cell based assays including tuberculin skin test and interferon-gamma release assays have their role primarily in the diagnosis of latent TB. Biomarkers are the latest addition in the battery of TB diagnostic tests facilitating diagnosis using easily accessible samples like urine, blood and breath of patients. Many biomarkers are still under evaluation and some of them are found to have a potential role as promising diagnostic tests of future.

The application of metabolomics toward pulmonary tuberculosis research

In the quest to identify novel biomarkers for pulmonary tuberculosis (TB), high-throughput systems biology approaches such as metabolomics has become increasingly widespread. Such biomarkers have not only successfully been used for better disease characterization, but have also provided new insights toward the future development of improved diagnostic and therapeutic approaches. In this review, we give a summary of the metabolomics studies done to date, with a specific focus on those investigating various aspects of pulmonary TB, and the infectious agent responsible, Mycobacterium tuberculosis. These studies, done on a variety of sample matrices, including bacteriological culture, sputum, blood, urine, tissue, and breath, are discussed in terms of their intended research outcomes or future clinical applications. Additionally, a summary of the research model, sample cohort, analytical apparatus and statistical methods used for biomarker identification in each of these studies, is provided.

GC-MS application in determination of volatile profiles emitted by infected and uninfected human tissue

Volatile organic compounds (VOCs) released into the headspace air over human tissues infected with different bacteria were investigated in this work. The above-mentioned VOCs result both from bacterial metabolic processes (pathogen-specific signals) and from the matrix (tissue samples themselves). The objective of this study was to investigate whether one could reliably identify various microorganism strains that exist inside infected tissue samples by direct monitoring of the headspace atmosphere above their cultures. Headspace samples were directly interrogated using a GC-MS system, which produced distinct profiles for samples contaminated with single bacterial strains or with multiple strains (mixed infections). Principal component analysis (PCA) and predictive analysis based on receiver operating characteristics curves (ROC) were the statistical procedures utilized for differentiating between infected and uninfected samples, while network analysis and heat-mapping were used to highlight the connections between emitted volatiles and infectious pathogens. By using ROC curves, obtained results demonstrated that the area under the ROC (95% probability interval) was 0.86 in case of infected samples and 0.48 for uninfected samples. On the other hand, PCA highlighted separation between components coming from infected and uninfected patients, where 67% of variance was described from the first 2 principal components. The biomarker chemicals documented from this work, as well as the developed methodology may ultimately be applied to identify bacterial infections by analyzing exhaled breath.

A systematic review of biomarkers to detect active tuberculosis

Millions of cases of tuberculosis (TB) go undiagnosed each year. Better diagnostic tools are urgently needed. Biomarker-based or multiple marker biosignature-based tests, ideally performed on blood or urine, for the detection of active TB might help to meet target product profiles proposed by the World Health Organization for point-of-care testing. We conducted a systematic review to summarize evidence on proposed biomarkers and biosignatures and evaluate their quality and level of evidence. We screened the titles and abstracts of 7,631 citations and included 443 publications that fulfilled the inclusion criteria and were published in 2010-2017. The types of biomarkers identified included antibodies, cytokines, metabolic activity markers, mycobacterial antigens and volatile organic compounds. Only 47% of studies reported a culture-based reference standard and diagnostic sensitivity and specificity. Forty-four biomarkers (4%) were identified in high-quality studies and met the target product profile minimum criteria, of which two have been incorporated into commercial assays. Of the 44 highest-quality biomarkers, 24 (55%) were multiple marker biosignatures. No meta-analyses were performed owing to between-study heterogeneity. In conclusion, TB biomarker discovery studies are often poorly designed and findings are rarely confirmed in independent studies. Few markers progress to a further developmental stage. More validation studies that consider the intended diagnostic use cases and apply rigorous design are needed. The extracted data from this review are currently being used by FIND as the foundation of a dynamic database in which biomarker data and developmental status will be presented.

Multisensory Gas Chromatography for Field Analysis of Complex Gaseous Mixtures

A novel approach to analysis of complex gaseous mixtures is presented. The approach is based on the utilization of a compact gas chromatograph in combination with an array of highly integrated and selective metal oxide (MOX) sensors. Thanks to the implementation of a multisensory detector, the device collects multiple chromatograms in a single run. The sensors in the integrated MEMS platform are very distinct in their catalytic properties. Hence, the time separation by chromatographic column is complemented by catalytic separation by a multisensory detector. Furthermore, the device can perform the analysis in a broad range of concentrations, from ppb to hundreds of ppm. Low ppb and even sub-ppb levels of detection for some analytes were achieved. As a part of this effort, nanocomposite gas sensors were synthesized for selective detection of hydrogen sulfide, mercaptans, alcohols, ketones, and heavy hydrocarbons.

Use of faecal volatile organic compound analysis for ante-mortem discrimination between CWD-positive, -negative exposed, and -known negative white-tailed deer (Odocoileus virginianus)

Chronic wasting disease (CWD) is a naturally occurring infectious, fatal, transmissible spongiform encephalopathy of cervids. Currently, disease confirmation relies on post-mortem detection of infectious prions in the medial retropharyngeal lymph nodes or obex in the brain via immunohistochemistry (IHC). Detection of CWD in living animals using this method is impractical, and IHC and other experimental assays are not reliable in detecting low concentrations of prion present in biofluids or faeces. Here, we evaluate the capability of faecal volatile organic compound analysis to discriminate between CWD-positive and -exposed white-tailed deer located at two positive cervid farms, and two groups of CWD-negative deer from two separate disease-free farms.

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.

Ionic Liquid-Carbon Nanotube Sensor Arrays for Human Breath Related Volatile Organic Compounds

High sensitivity, selectivity, and stability are key requirements for carbon nanotube (CNT)-based sensors to realize their full potential in applications ranging from chemical warfare agent detection to disease diagnostics. Herein we demonstrate the sensing of volatile organic compounds (VOCs) relevant to human diseases using an array of chemiresistive carbon nanotube (CNT)-based sensors functionalized with ionic liquids (ILs). The ILs are fluid at ambient temperature and were selected to produce a discriminating sensor array capable of the gas-phase detection of human disease-related VOCs. We find that sensor arrays consisting of imidazolium-based ILs with different substituents and counterions provide selective responses for known biomarkers of infectious diseases of the lungs. Specifically, the sensors discriminate the various volatile biomarkers for tuberculosis based on their polarity, solubility, and chemical affinities. In addition to selectivity, the sensors also show a high level of reversibility and promising long-term stability, which renders them to be suitable candidates for practical applications in breath analysis.

Exhaled human breath analysis in active pulmonary tuberculosis diagnostics by comprehensive gas chromatography-mass spectrometry and chemometric techniques

Tuberculosis (TB) is the deadliest infectious disease, and yet accurate diagnostics for the disease are unavailable for many subpopulations. In this study, we investigate the possibility of using human breath for the diagnosis of active TB among TB suspect patients, considering also several risk factors for TB for smokers and those with human immunodeficiency virus (HIV). The analysis of exhaled breath, as an alternative to sputum-dependent tests, has the potential to provide a simple, fast, non-invasive, and readily available diagnostic service that could positively change TB detection. A total of 50 individuals from a clinic in South Africa were included in this pilot study. Human breath has been investigated in the setting of active TB using the thermal desorption-comprehensive two-dimensional gas chromatography-time of flight mass spectrometry methodology and chemometric techniques. From the entire spectrum of volatile metabolites in breath, three machine learning algorithms (support vector machines, partial least squares discriminant analysis, and random forest) to select discriminatory volatile molecules that could potentially be useful for active TB diagnosis were employed. Random forest showed the best overall performance, with sensitivities of 0.82 and 1.00 and specificities of 0.92 and 0.60 in the training and test data respectively. Unsupervised analysis of the compounds implicated by these algorithms suggests that they provide important information to cluster active TB from other patients. These results suggest that developing a non-invasive diagnostic for active TB using patient breath is a potentially rich avenue of research, including among patients with HIV comorbidities.

Mycobacteria-derived biomarkers for tuberculosis diagnosis

Tuberculosis (TB) remains an escalating problem worldwide. The current diagnostic methods do not always guarantee reliable diagnosis. TB treatment is a time-consuming process that requires the use of several chemotherapeutics, to which mycobacteria are becoming increasingly resistant. This article focuses on the potential utility of biomarkers of mycobacterial origin with potential implications for TB diagnosis. Properly standardized indicators could become new diagnostic tools, improving and streamlining the identification of Mycobacterium tuberculosis infection and the implementation of appropriate therapy. These markers can also potentially provide a quick confirmation of effectiveness of new anti-mycobacterial drugs and TB vaccines, leading to a possible application in practice.

Metabolomics applied to the discovery of tuberculosis and diabetes mellitus biomarkers

Tuberculosis (TB) and diabetes mellitus Type 2 (DM2) are two diseases as ancient as they are harmful to human health. The outcome for both diseases in part depends on immune and metabolic individual responses. DM2 is increasing yearly, mainly due to environmental, genetic and lifestyle habits. There are multiple evidence that DM2 is one of the most important risk factor of becoming infected with TB or reactivating latent TB. Mass spectrometry-based metabolomics is an important tool for elucidating the metabolites and metabolic pathways that influence the immune responses to M. tuberculosis infection during diabetes. We provide an up-to-date review highlighting the importance and benefit of metabolomics for identifying biomarkers as candidate molecules for diagnosis, disease activity or prognosis.

Volatile Decay Products in Breath During Peritonitis Shock are Attenuated by Enteral Blockade of Pancreatic Digestive Proteases

There is a need to develop markers for early detection of organ failure in shock that can be noninvasively measured at point of care. We explore here the use of volatile organic compounds (VOCs) in expired air in a rat peritonitis shock model. Expired breath samples were collected into Tedlar gas bags and analyzed by standardized gas chromatography. The gas chromatograms were digitally analyzed for presence of peak amounts over a range of Kovach indices. Following the induction of peritonitis, selected volatile compounds were detected within about 1 h, which remained at elevated amounts over a 6 h observation period. These VOCs were not present in control animals without peritonitis. Comparisons with know VOCs indicate that they include 1,4-diaminobutane and trimethylamine N-oxide. When pancreatic digestive proteases were blocked with tranexamic acid in the intestine and peritoneum, a procedure that serves to reduce organ failure in shock, the amounts of VOCs in the breath decreased spontaneously to control values without peritonitis. These results indicate that peritonitis shock is accompanied by development of volatile organic compounds that may be generated by digestive enzymes in the small intestine. VOCs may serve as indicators for detection of early forms of autodigestion by digestive proteases.

Pancreatic ductal adenocarcinoma can be detected by analysis of volatile organic compounds (VOCs) in alveolar air

Background

In the last decade many studies showed that the exhaled breath of subjects suffering from several pathological conditions has a peculiar volatile organic compound (VOC) profile. The objective of the present work was to analyse the VOCs in alveolar air to build a diagnostic tool able to identify the presence of pancreatic ductal adenocarcinoma in patients with histologically confirmed disease.

Methods

The concentration of 92 compounds was measured in the end-tidal breath of 65 cases and 102 controls. VOCs were measured with an ion-molecule reaction mass spectrometry. To distinguish between subjects with pancreatic adenocarcinomas and controls, an iterated Least Absolute Shrinkage and Selection Operator multivariate Logistic Regression model was elaborated.

Results

The final predictive model, based on 10 VOCs, significantly and independently associated with the outcome had a sensitivity and specificity of 100 and 84% respectively, and an area under the ROC curve of 0.99. For further validation, the model was run on 50 other subjects: 24 cases and 26 controls; 23 patients with histological diagnosis of pancreatic adenocarcinomas and 25 controls were correctly identified by the model.

Conclusions

Pancreatic cancer is able to alter the concentration of some molecules in the blood and hence of VOCs in the alveolar air in equilibrium. The detection and statistical rendering of alveolar VOC composition can be useful for the clinical diagnostic approach of pancreatic neoplasms with excellent sensitivity and specificity.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4452-0) contains supplementary material, which is available to authorized users.

Mass Spectrometric Identification of Urinary Biomarkers of Pulmonary Tuberculosis

Background

Tuberculosis (TB) is the leading infectious cause of death worldwide. A major barrier to control of the pandemic is a lack of clinical biomarkers with the ability to distinguish active TB from healthy and sick controls and potential for development into point-of-care diagnostics.

Methods

We conducted a prospective case control study to identify candidate urine-based diagnostic biomarkers of active pulmonary TB (discovery cohort) and obtained a separate blinded “validation” cohort of confirmed cases of active pulmonary TB and controls with non-tuberculous pulmonary disease for validation. Clean-catch urine samples were collected and analyzed using high performance liquid chromatography-coupled time-of-flight mass spectrometry.

Results

We discovered ten molecules from the discovery cohort with receiver-operator characteristic (ROC) area-under-the-curve (AUC) values >85%. These 10 molecules also significantly decreased after 60 days of treatment in a subset of 20 participants followed over time. Of these, a specific combination of diacetylspermine, neopterin, sialic acid, and N-acetylhexosamine exhibited ROC AUCs >80% in a blinded validation cohort of participants with active TB and non-tuberculous pulmonary disease.

Conclusion

Urinary levels of diacetylspermine, neopterin, sialic acid, and N-acetylhexosamine distinguished patients with tuberculosis from healthy controls and patients with non-tuberculous pulmonary diseases, providing a potential noninvasive biosignature of active TB.

Funding

This study was funded by Weill Cornell Medicine, the National Institute of Allergy and Infectious Diseases, the Clinical and Translational Science Center at Weill Cornell, the NIH Fogarty International Center grants, and the NIH Tuberculosis Research Unit (Tri-I TBRU).

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Urinary levels of small metabolites appear capable of distinguishing cases of active pulmonary tuberculosis from sick and healthy controls.

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Levels of these biomarkers decrease after 60 days of treatment in a longitudinal cohort of 20 participants.

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- Many of the identified biomarkers are known inflammatory intermediates that may reflect a specific immune response to tuberculosis.

Urine tests are commonly used to enable non-invasive, rapid and point-of-care diagnosis of various infectious diseases. We identified diacetylspermine, neopterin, sialic acid and N-acetylhexosamine as potential urine-based biomarkers for tuberculosis from two independent patient cohorts. These metabolites are known inflammatory intermediates and appear to decrease with anti-tuberculosis therapy in a subset of participants followed over 2 months. If validated, these metabolites have potential to both improve our understanding of the immune reaction to active tuberculosis and facilitate the development of a much-needed clinical biomarker for tuberculosis.

Machine learning for the meta-analyses of microbial pathogens' volatile signatures

Non-invasive and fast diagnostic tools based on volatolomics hold great promise in the control of infectious diseases. However, the tools to identify microbial volatile organic compounds (VOCs) discriminating between human pathogens are still missing. Artificial intelligence is increasingly recognised as an essential tool in health sciences. Machine learning algorithms based in support vector machines and features selection tools were here applied to find sets of microbial VOCs with pathogen-discrimination power. Studies reporting VOCs emitted by human microbial pathogens published between 1977 and 2016 were used as source data. A set of 18 VOCs is sufficient to predict the identity of 11 microbial pathogens with high accuracy (77%), and precision (62-100%). There is one set of VOCs associated with each of the 11 pathogens which can predict the presence of that pathogen in a sample with high accuracy and precision (86-90%). The implemented pathogen classification methodology supports future database updates to include new pathogen-VOC data, which will enrich the classifiers. The sets of VOCs identified potentiate the improvement of the selectivity of non-invasive infection diagnostics using artificial olfaction devices.

Update on tuberculosis biomarkers: From correlates of risk, to correlates of active disease and of cure from disease

Tuberculosis (TB) remains a devastating disease, yet despite its enormous toll on global health, tools to control TB are insufficient and often outdated. TB Biomarkers (TB-BM) would constitute extremely useful tools to measure infection status and predict outcome of infection, vaccination or therapy. There are several types of TB-BM: Correlate of Infection; Correlate of TB Disease; Correlate of Increased Risk of Developing Active TB Disease; Correlate of the Curative Response to Therapy; and Correlate of Protection (CoP). Most TB-BM currently studied are host-derived BM, and consist of transcriptomic, proteomic, metabolomic, cellular markers or marker combinations ('signatures'). In particular, vaccine-inducible CoP are expected to be transformative in developing new TB vaccines as they will de-risk vaccine research and development (R&D) as well as human testing at an early stage. In addition, CoP could also help minimizing the need for preclinical studies in experimental animals. Of key importance is that TB-BM are tested and validated in different well-characterized human TB cohorts, preferably with complementary profiles and geographically diverse populations: genetic and environmental factors such as (viral) coinfections, exposure to non-tuberculous mycobacteria, nutritional status, metabolic status, age (infants vs children vs adolescents vs adults) and other factors impact host immune set points and host responses across different populations. In this study, we review the most recent advances in research into TB-BM for the diagnosis of active TB, risk of TB development and treatment-induced TB cure.

Towards the use of breath for detecting mycobacterial infection: a case study in a murine model

In the present research, the potential of breath analysis by comprehensive two-dimensional gas chromatography coupled to mass spectrometry (GC×GC-MS) was investigated for the discrimination between healthy and infected mice. A pilot study employing a total of 16 animals was used to develop a method for breath analysis in a murine model for studying Mycobacterium tuberculosis complex (MTBC) using the M. bovis bacillus Calmette-Guérin. Breath was collected in Tedlar bags and concentrated onto thermal desorption tubes for subsequent analysis by GC×GC-MS. Immunological test and bacterial cell count in bronchoalveolar lavage fluid and mice lung homogenate confirmed the presence of bacteria in the infected group. From the GC×GC-MS analysis, 23 molecules were found to mainly drive the separation between control and infected mice and their tentative identification is provided.This study shows that the overall used methodology is able to differentiate breath between healthy and infected animals, and the information herein can be used to further develop the mouse breath model to study MTBC pathogenesis, evaluate pre-clinical drug regimen efficacy, and to further develop the concept of breath-based diagnostics.

Diagnostic accuracy of breath tests for pneumoconiosis using an electronic nose

Breath analyses have attracted substantial attention as screens for occupational environmental lung disease. The objective of this study was to develop breath tests for pneumoconiosis by analysing volatile organic compounds using an electronic nose. A case-control study was designed. We screened 102 subjects from a cohort of stone workers. After excluding three subjects with poorly controlled diabetes mellitus and one subject with asthma, 98 subjects were enrolled, including 34 subjects with pneumoconiosis and 64 healthy controls. We analysed the subjects' breath using an electronic nose with 32 nanocomposite sensors. Data were randomly split into 80% for model building and 20% for validation. Using a linear discriminate analysis, the sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUROC) were 67.9%, 88.0%, 80.8%, and 0.91, respectively, in the training set and 66.7%, 71.4%, 70.0%, and 0.86, respectively, in the test set. In subgroup analysis divided by smoking status, the AUROCs for current smokers, former smokers, and subjects who never smoked were 0.94, 0.93, and 0.99, respectively. In subgroup analysis divided by gender, the AUROCs for males and females were 0.95 and 0.99, respectively. Breath tests may have potential as a screen for pneumoconiosis. A multi-centre study is warranted, and the procedures must be standardized before clinical application.

Development of breath test for pneumoconiosis: a case-control study

Background

Lipid peroxidation plays an important role in the pathogenesis of pneumoconiosis. Volatile organic compounds (VOCs) generated from lipid peroxidation might be used to detect pneumoconiosis. The objective of this study was to develop a breath test for pneumoconiosis.

Methods

A case-control study was designed. Breath and ambient air were analysed by gas chromatography/mass spectrometry. After blank correction to prevent contamination from ambient air, we used canonical discriminant analysis (CDA) to assess the discrimination accuracy and principal component analysis (PCA) to generate a prediction score. The prediction accuracy was calculated and validated using the International Classification of Radiographs of the Pneumoconiosis criteria combined with an abnormal pulmonary function test as a reference standard. We generated a receiver operator characteristic (ROC) curve and calculated the area under the ROC curve (AUC) to estimate the screening accuracy of the breath test.

Results

We enrolled 200 stone workers. After excluding 5 subjects with asthma and 16 subjects who took steroids or nonsteroidal anti-inflammatory drugs, a total of 179 subjects were used in the final analyses, which included 25 cases and 154 controls. By CDA, 88.8% of subjects were correctly discriminated by their exposure status and the presence of pneumoconiosis. After excluding the VOCs of automobile exhaust and cigarette smoking, pentane and C5-C7 methylated alkanes constituted the major VOCs in the breath of persons with pneumoconiosis. Using the prediction score generated from PCA, the ROC-AUC was 0.88 (95% CI = 0.80—0.95), and the mean ROC-AUC of 5-fold cross-validation was 0.90. The breath test had good accuracy for pneumoconiosis diagnosis.

Conclusion

The analysis of breath VOCs has potential in the screening of pneumoconiosis for its non-invasiveness and high accuracy. We suggest that a multi-centre study is warranted and that all procedures must be standardized before clinical application.

Exhaled Volatile Organic Compounds of Infection: A Systematic Review

With heightened global concern of microbial drug resistance, advanced methods for early and accurate diagnosis of infection are urgently needed. Analysis of exhaled breath volatile organic compounds (VOCs) toward detecting microbial infection potentially allows a highly informative and noninvasive alternative to current genomics and culture-based methods. We performed a systematic review of research literature reporting human and animal exhaled breath VOCs related to microbial infections. In this Review, we find that a wide range of breath sampling and analysis methods are used by researchers, which significantly affects interstudy method comparability. Studies either perform targeted analysis of known VOCs relating to an infection, or non-targeted analysis to obtain a global profile of volatile metabolites. In general, the field of breath analysis is still relatively immature, and there is much to be understood about the metabolic production of breath VOCs, particularly in a host where both commensal microflora as well as pathogenic microorganisms may be manifested in the airways. We anticipate that measures to standardize high throughput sampling and analysis, together with an increase in large scale collaborative international trials, will bring routine breath VOC analysis to improve diagnosis of infection closer to reality.

Inflammatory bowel disease and patterns of volatile organic compounds in the exhaled breath of children: A case-control study using Ion Molecule Reaction-Mass Spectrometry

Inflammatory bowel diseases (IBD) profoundly affect quality of life and have been gradually increasing in incidence, prevalence and severity in many areas of the world, and in children in particular. Patients with suspected IBD require careful history and clinical examination, while definitive diagnosis relies on endoscopic and histological findings. The aim of the present study was to investigate whether the alveolar air of pediatric patients with IBD presents a specific volatile organic compounds’ (VOCs) pattern when compared to controls. Patients 10–17 years of age, were divided into four groups: Crohn’s disease (CD), ulcerative colitis (UC), controls with gastrointestinal symptomatology, and surgical controls with no evidence of gastrointestinal problems. Alveolar breath was analyzed by ion molecule reaction mass spectrometry. Four models were built starting from 81 molecules plus the age of subjects as independent variables, adopting a penalizing LASSO logistic regression approach: 1) IBDs vs. controls, finally based on 18 VOCs plus age (sensitivity = 95%, specificity = 69%, AUC = 0.925); 2) CD vs. UC, finally based on 13 VOCs plus age (sensitivity = 94%, specificity = 76%, AUC = 0.934); 3) IBDs vs. gastroenterological controls, finally based on 15 VOCs plus age (sensitivity = 94%, specificity = 65%, AUC = 0.918); 4) IBDs vs. controls, built starting from the 21 directly or indirectly calibrated molecules only, and finally based on 12 VOCs plus age (sensitivity = 94%, specificity = 71%, AUC = 0.888). The molecules identified by the models were carefully studied in relation to the concerned outcomes. This study, with the creation of models based on VOCs profiles, precise instrumentation and advanced statistical methods, can contribute to the development of new non–invasive, fast and relatively inexpensive diagnostic tools, with high sensitivity and specificity. It also represents a crucial step towards gaining further insights on the etiology of IBD through the analysis of specific molecules which are the expression of the particular metabolism that characterizes these patients.

Mass spectrometric techniques for the analysis of volatile organic compounds emitted from bacteria

Bacteria are the main cause of many human diseases. Typical bacterial identification methods, for example culture-based, serological and genetic methods, are time-consuming, delaying the potential for an early and accurate diagnosis and the appropriate subsequent treatment. Nevertheless, there is a stringent need for in situ tests that are rapid, noninvasive and sensitive, which will greatly facilitate timely treatment of the patients. This review article presents volatile organic metabolites emitted from various micro-organism strains responsible for common bacterial infections in humans. Additionally, the manuscript shows the application of different analytical techniques for fast bacterial identification. Details of these techniques are given, which focuses on their advantages and drawbacks in using for volatile organic components analysis.

Use of fecal volatile organic compound analysis to discriminate between non-vaccinated and BCG-Vaccinated cattle prior to and after Mycobacterium bovis challenge

Bovine tuberculosis is a zoonotic disease of global public health concern. Development of diagnostic tools to improve test accuracy and efficiency in domestic livestock and enable surveillance of wildlife reservoirs would improve disease management and eradication efforts. Use of volatile organic compound analysis in breath and fecal samples is being developed and optimized as a means to detect disease in humans and animals. In this study we demonstrate that VOCs present in fecal samples can be used to discriminate between non-vaccinated and BCG-vaccinated cattle prior to and after Mycobacterium bovis challenge.

The volatile molecule signature of four mycobacteria species

Mycobacteria are the leading cause of death from infectious disease worldwide and limitations in current diagnostics are hampering control efforts. In recent years, the use of small volatile molecules as diagnostic biomarkers for mycobacteria has shown promise for use in the rapid analysis of in vitro cultures as well as ex vivo diagnosis using breath or sputum. In this study, 18 strains from four mycobacteria species (Mycobacterium avium, M. bovis BCG, M. intracellulare and M. xenopi) were analyzed for the first time using two-dimensional gas chromatography time-of-flight mass spectrometry (GC × GC-TOFMS). This study represents the first time volatile molecules associated with M. intracellulare and M. xenopi have ever been reported. A total of 217 chromatographic features were identified and 58 features were selected that discriminate between these four species. Putative identifications are provided for 17 of the 58 discriminatory features, three of which have been reported previously in mycobacteria. The identification of mycobacteria-associated volatile biomarker suites could reduce the time-to-diagnosis for mycobacterial infections, either from in vitro cultures prior to the visualization of colonies or directly from ex vivo specimens, thereby shortening the empiric treatment window and potentially improving outcomes.

Volatolomics of breath as an emerging frontier in pulmonary arterial hypertension

There is accumulating evidence in support of the significant improvement in survival rates and clinical outcomes when pulmonary arterial hypertension (PAH) is diagnosed at early stages. Nevertheless, it remains a major clinical challenge and the outcomes are dependent on invasive right heart catheterisation.

Resulting from pathophysiological processes and detectable in exhaled breath, volatile organic compounds (VOCs) have been proposed as noninvasive biomarkers for PAH. Studies have confirmed significant alterations of the exhaled VOCs among PAH patients when compared to controls and/or patients with other respiratory diseases. This suggests exhaled breath analysis as a potential noninvasive medical application in the field of PAH.

In this article, we review and discuss the progress made so far in the field of exhaled volatolomics (the omics of VOCs) as a potential noninvasive diagnostics of PAH. In addition, we propose a model including possible biochemical pathways on the level of the remodelled artery, in which specific VOCs could be detectable in exhaled breath during the early phases of PAH. We debate the different analytical approaches used and recommend a diagram including a “bottom–top” strategy, from basic to translational studies, required for promoting the field.

Exhaled Breath Metabolomics for the Diagnosis of Pneumonia in Intubated and Mechanically-Ventilated Intensive Care Unit (ICU)-Patients

The diagnosis of hospital-acquired pneumonia remains challenging. We hypothesized that analysis of volatile organic compounds (VOCs) in exhaled breath could be used to diagnose pneumonia or the presence of pathogens in the respiratory tract in intubated and mechanically-ventilated intensive care unit patients. In this prospective, single-centre, cross-sectional cohort study breath from mechanically ventilated patients was analysed using gas chromatography-mass spectrometry. Potentially relevant VOCs were selected with a p-value < 0.05 and an area under the receiver operating characteristics curve (AUROC) above 0.7. These VOCs were used for principal component analysis and partial least square discriminant analysis (PLS-DA). AUROC was used as a measure of accuracy. Ninety-three patients were included in the study. Twelve of 145 identified VOCs were significantly altered in patients with pneumonia compared to controls. In colonized patients, 52 VOCs were significantly different. Partial least square discriminant analysis classified patients with modest accuracy (AUROC: 0.73 (95% confidence interval (CI): 0.57–0.88) after leave-one-out cross-validation). For determining the colonization status of patients, the model had an AUROC of 0.69 (95% CI: 0.57–0.82) after leave-one-out cross-validation. To conclude, exhaled breath analysis can be used to discriminate pneumonia from controls with a modest to good accuracy. Furthermore breath profiling could be used to predict the presence and absence of pathogens in the respiratory tract. These findings need to be validated externally.

Stable isotope profiles reveal active production of VOCs from human-associated microbes

Volatile organic compounds (VOCs) measured from exhaled breath have great promise for the diagnosis of bacterial infections. However, determining human or microbial origin of VOCs detected in breath remains a great challenge. For example, the microbial fermentation product 2,3-butanedione was recently found in the breath of Cystic Fibrosis (CF) patients; parallel culture-independent metagenomic sequencing of the same samples revealed that Streptococcus and Rothia spp. have the genetic capacity to produce 2,3-butanedione. To investigate whether the genetic capacity found in metagenomes translates to bacterial production of a VOC of interest such as 2,3-butanedione, we fed stable isotopes to three bacterial strains isolated from patients: two gram-positive bacteria, Rothia mucilaginosa and Streptococcus salivarius, and a dominant opportunistic gram-negative pathogen, Pseudomonas aeruginosa. Culture headspaces were collected and analyzed using a gas chromatographic system to quantify the abundance of VOCs of interest; mass spectroscopy was used to determine whether the stable isotope label had been incorporated. Our results show that R. mucilaginosa and S. salivarius consumed D-Glucose-¹³C₆ to produce labeled 2,3-butanedione. R. mucilaginosa and S. salivarius also produced labeled acetaldehyde and ethanol when grown with ²H₂O. Additionally, we find that P. aeruginosa growth and dimethyl sulfide production are increased when exposed to lactic acid in culture. These results highlight the importance VOCs produced by P. aeruginosa, R. mucilaginosa, and S. salivarius as nutrients and signals in microbial communities, and as potential biomarkers in a CF infection.

A Compendium of Volatile Organic Compounds (VOCs) Released By Human Cell Lines

Volatile organic compounds (VOCs) offer unique insights into ongoing biochemical processes in healthy and diseased humans. Yet, their diagnostic use is hampered by the limited understanding of their biochemical or cellular origin and their frequently unclear link to the underlying diseases. Major advancements are expected from the analyses of human primary cells, cell lines and cultures of microorganisms. In this review, a database of 125 reliably identified VOCs previously reported for human healthy and diseased cells was assembled and their potential origin is discussed. The majority of them have also been observed in studies with other human matrices (breath, urine, saliva, feces, blood, skin emanations). Moreover, continuing improvements of qualitative and quantitative analyses, based on the recommendations of the ISO-11843 guidelines, are suggested for the necessary standardization of analytical procedures and better comparability of results. The data provided contribute to arriving at a more complete human volatilome and suggest potential volatile biomarkers for future validation.

Dedication: This review is dedicated to the memory of Prof. Dr. Anton Amann, who sadly passed away on January 6, 2015. He was motivator and motor for the field of breath research.

Metabolomics biomarkers for tuberculosis diagnostics: current status and future objectives

Numerous studies have contributed to our current understanding of the complex biology of pulmonary tuberculosis and subsequently provided solutions to its control or eradication. Metabolomics, a newcomer to the Omics research domain, has significantly contributed to this understanding by identifying biomarkers originating from the disease-associated metabolome adaptations of both the microbe and host. These biomarkers have shed light on previously unknown disease mechanisms, many of which have been implemented toward the development of improved diagnostic strategies. In this review, we will discuss the role that metabolomics has played in tuberculosis research to date, with a specific focus on new biomarker identification, and how these have contributed to improved disease characterization and diagnostics, and their potential clinical applications.

Diagnosis and Classification of 17 Diseases from 1404 Subjects via Pattern Analysis of Exhaled Molecules

We report on an artificially intelligent nanoarray based on molecularly modified gold nanoparticles and a random network of single-walled carbon nanotubes for noninvasive diagnosis and classification of a number of diseases from exhaled breath. The performance of this artificially intelligent nanoarray was clinically assessed on breath samples collected from 1404 subjects having one of 17 different disease conditions included in the study or having no evidence of any disease (healthy controls). Blind experiments showed that 86% accuracy could be achieved with the artificially intelligent nanoarray, allowing both detection and discrimination between the different disease conditions examined. Analysis of the artificially intelligent nanoarray also showed that each disease has its own unique breathprint, and that the presence of one disease would not screen out others. Cluster analysis showed a reasonable classification power of diseases from the same categories. The effect of confounding clinical and environmental factors on the performance of the nanoarray did not significantly alter the obtained results. The diagnosis and classification power of the nanoarray was also validated by an independent analytical technique, i.e., gas chromatography linked with mass spectrometry. This analysis found that 13 exhaled chemical species, called volatile organic compounds, are associated with certain diseases, and the composition of this assembly of volatile organic compounds differs from one disease to another. Overall, these findings could contribute to one of the most important criteria for successful health intervention in the modern era, viz. easy-to-use, inexpensive (affordable), and miniaturized tools that could also be used for personalized screening, diagnosis, and follow-up of a number of diseases, which can clearly be extended by further development.

A new method to evaluate macaque health using exhaled breath: A case study of M. tuberculosis in a BSL-3 setting

Breath is hypothesized to contain clinically relevant information, useful for the diagnosis and monitoring of disease, as well as understanding underlying pathogenesis. Nonhuman primates, such as the cynomolgus macaque, serve as an important model for the study of human disease, including over 70 different human infections. In this feasibility study, exhaled breath was successfully collected in less than 5 min under Biosafety Level 3 conditions from five anesthetized, intubated cynomolgus and rhesus macaques, before and after lung infection with M. tuberculosis The breath was subsequently analyzed using comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry. A total of 384 macaque breath features were detected, with hydrocarbons being the most abundant. We provide putative identification for 19 breath molecules and report on overlap between the identified macaque breath compounds and those identified in previous human studies.NEW & NOTEWORTHY To the best of our knowledge, this is the first time the volatile molecule content of macaque breath has been comprehensively sampled and analyzed. We do so here in a Biosafety Level 3 setting in the context of M. tuberculosis lung infection. The breath of nonhuman primates represents a novel fluid that could provide insight into disease pathogenesis.

Elucidating the biosynthetic pathways of volatile organic compounds in Mycobacterium tuberculosis through a computational approach

A first report on the biosynthetic origin ofMycobacterium tuberculosisspecific small volatile molecules.

Comparison of volatile organic compounds from lung cancer patients and healthy controls-challenges and limitations of an observational study

This paper outlines the design and performance of an observational study on the profiles of volatile organic compounds (VOCs) in the breath of 37 lung cancer patients and 23 healthy controls of similar age. The need to quantify each VOC considered as a potential disease marker on the basis of individual calibration is elaborated, and the quality control measures required to maintain reproducibility in breath sampling and subsequent instrumental trace VOC analysis using solid phase microextraction-gas chromatography-mass spectrometry over a study period of 14 months are described. Twenty-four VOCs were quantified on the basis of their previously suggested potential as cancer markers. The concentration of aromatic compounds in the breath was increased, as expected, in smokers, while lung cancer patients displayed significantly increased levels of oxygenated VOCs such as aldehydes, 2-butanone and 1-butanol. Although sets of selected oxygenated VOCs displayed sensitivities and specificities between 80% and 90% using linear discriminant analysis (LDA) with leave-one-out cross validation, the effective selectivity of the breath VOC approach with regard to cancer detection is clearly limited. Results are discussed against the background of the literature on volatile cancer marker investigations and the prospects of linking increased VOC levels in patients' breath with approaches that employ sniffer dogs. Experience from this study and the literature suggests that the currently available methodology is not able to use breath VOCs to reliably discriminate between cancer patients and healthy controls. Observational studies often tend to note significant differences in levels of certain oxygenated VOCs, but without the resolution required for practical application. Any step towards the exploitation of differences in VOC profiles for illness detection would have to solve current restrictions set by the low and variable VOC concentrations. Further challenges are the technical complexity of studies involving breath sampling and possibly the limited capability of current analytical procedures to detect unstable marker candidates.

Tuberculosis Biomarkers: From Diagnosis to Protection

New approaches to control tuberculosis (TB) worldwide are needed. In particular, new tools for diagnosis and new biomarkers are required to evaluate both pathogen and host key elements of the response to infection. Non-sputum based diagnostic tests, biomarkers predictive of adequate responsiveness to treatment, and biomarkers of risk of developing active TB disease are major goals. Here, we review the current state of the field. Although reports on new candidate biomarkers are numerous, validation and independent confirmation are rare. Efforts are needed to reduce the gap between the exploratory up-stream identification of candidate biomarkers, and the validation of biomarkers against clear clinical endpoints in different populations. This will need a major commitment from both scientists and funding bodies.

Bacterial volatiles and diagnosis of respiratory infections

Breath testing has enormous potential in the medical diagnostic field. The underlying complexity and perceived availability of adequate specimens, combined with a lack of knowledge of the metabolic pathways that give rise to compounds that are sources of analytes detectable in breath, has greatly slowed development. These real obstacles have recently been largely overcome in the use of breath testing to identify patients with cystic fibrosis associated Pseudomonas aeruginosa infection and tuberculosis. This review summarizes progress made in the characterization of microbial volatiles produced by major lower respiratory tract bacterial pathogens, and their potential use as diagnostic markers in patient breath testing.

Diagnostic 'omics' for active tuberculosis

The decision to treat active tuberculosis (TB) is dependent on microbiological tests for the organism or evidence of disease compatible with TB in people with a high demographic risk of exposure. The tuberculin skin test and peripheral blood interferon-γ release assays do not distinguish active TB from a cleared or latent infection. Microbiological culture of mycobacteria is slow. Moreover, the sensitivities of culture and microscopy for acid-fast bacilli and nucleic acid detection by PCR are often compromised by difficulty in obtaining samples from the site of disease. Consequently, we need sensitive and rapid tests for easily obtained clinical samples, which can be deployed to assess patients exposed to TB, discriminate TB from other infectious, inflammatory or autoimmune diseases, and to identify subclinical TB in HIV-1 infected patients prior to commencing antiretroviral therapy. We discuss the evaluation of peripheral blood transcriptomics, proteomics and metabolomics to develop the next generation of rapid diagnostics for active TB. We catalogue the studies published to date seeking to discriminate active TB from healthy volunteers, patients with latent infection and those with other diseases. We identify the limitations of these studies and the barriers to their adoption in clinical practice. In so doing, we aim to develop a framework to guide our approach to discovery and development of diagnostic biomarkers for active TB.

The use of a gas chromatography-sensor system combined with advanced statistical methods, towards the diagnosis of urological malignancies

Prostate cancer is one of the most common cancers. Serum prostate-specific antigen (PSA) is used to aid the selection of men undergoing biopsies. Its use remains controversial. We propose a GC-sensor algorithm system for classifying urine samples from patients with urological symptoms. This pilot study includes 155 men presenting to urology clinics, 58 were diagnosed with prostate cancer, 24 with bladder cancer and 73 with haematuria and or poor stream, without cancer. Principal component analysis (PCA) was applied to assess the discrimination achieved, while linear discriminant analysis (LDA) and support vector machine (SVM) were used as statistical models for sample classification. Leave-one-out cross-validation (LOOCV), repeated 10-fold cross-validation (10FoldCV), repeated double cross-validation (DoubleCV) and Monte Carlo permutations were applied to assess performance. Significant separation was found between prostate cancer and control samples, bladder cancer and controls and between bladder and prostate cancer samples. For prostate cancer diagnosis, the GC/SVM system classified samples with 95% sensitivity and 96% specificity after LOOCV. For bladder cancer diagnosis, the SVM reported 96% sensitivity and 100% specificity after LOOCV, while the DoubleCV reported 87% sensitivity and 99% specificity, with SVM showing 78% and 98% sensitivity between prostate and bladder cancer samples. Evaluation of the results of the Monte Carlo permutation of class labels obtained chance-like accuracy values around 50% suggesting the observed results for bladder cancer and prostate cancer detection are not due to over fitting. The results of the pilot study presented here indicate that the GC system is able to successfully identify patterns that allow classification of urine samples from patients with urological cancers. An accurate diagnosis based on urine samples would reduce the number of negative prostate biopsies performed, and the frequency of surveillance cystoscopy for bladder cancer patients. Larger cohort studies are planned to investigate the potential of this system. Future work may lead to non-invasive breath analyses for diagnosing urological conditions.

A review of clinical models for the evaluation of human TB vaccines

While much progress has been made in the fight against the scourge of tuberculosis (TB), we are still some way from reaching the ambitious targets of eliminating it as a global public health problem by the mid twenty-first century. A new and effective vaccine that protects against pulmonary TB disease will be an essential element of any control strategy. Over a dozen vaccines are currently in development, but recent efficacy trial data from one of the most advanced candidates have been disappointing. Limitations of current preclinical animal models exist, together with a lack of a complete understanding of host immunity to TB or robust correlates of disease risk and protection. Therefore, in the context of such obstacles, we discuss the lessons identified from recent efficacy trials, current concepts of biomarkers and correlates of protection, the potential of innovative clinical models such as human challenge and conducting trials in high-incidence settings to evaluate TB vaccines in humans, and the use of systems vaccinology and novel technologies including transcriptomics and metabolomics, that may facilitate their utility.

Blinded Validation of Breath Biomarkers of Lung Cancer, a Potential Ancillary to Chest CT Screening

Background

Breath volatile organic compounds (VOCs) have been reported as biomarkers of lung cancer, but it is not known if biomarkers identified in one group can identify disease in a separate independent cohort. Also, it is not known if combining breath biomarkers with chest CT has the potential to improve the sensitivity and specificity of lung cancer screening.

Methods

Model-building phase (unblinded): Breath VOCs were analyzed with gas chromatography mass spectrometry in 82 asymptomatic smokers having screening chest CT, 84 symptomatic high-risk subjects with a tissue diagnosis, 100 without a tissue diagnosis, and 35 healthy subjects. Multiple Monte Carlo simulations identified breath VOC mass ions with greater than random diagnostic accuracy for lung cancer, and these were combined in a multivariate predictive algorithm. Model-testing phase (blinded validation): We analyzed breath VOCs in an independent cohort of similar subjects (n = 70, 51, 75 and 19 respectively). The algorithm predicted discriminant function (DF) values in blinded replicate breath VOC samples analyzed independently at two laboratories (A and B). Outcome modeling: We modeled the expected effects of combining breath biomarkers with chest CT on the sensitivity and specificity of lung cancer screening.

Results

Unblinded model-building phase. The algorithm identified lung cancer with sensitivity 74.0%, specificity 70.7% and C-statistic 0.78. Blinded model-testing phase: The algorithm identified lung cancer at Laboratory A with sensitivity 68.0%, specificity 68.4%, C-statistic 0.71; and at Laboratory B with sensitivity 70.1%, specificity 68.0%, C-statistic 0.70, with linear correlation between replicates (r = 0.88). In a projected outcome model, breath biomarkers increased the sensitivity, specificity, and positive and negative predictive values of chest CT for lung cancer when the tests were combined in series or parallel.

Conclusions

Breath VOC mass ion biomarkers identified lung cancer in a separate independent cohort, in a blinded replicated study. Combining breath biomarkers with chest CT could potentially improve the sensitivity and specificity of lung cancer screening.

Trial Registration

ClinicalTrials.gov NCT00639067