Asthma and COPD

Breath biomarkers offer a route to more effective personalized treatments

Asthma

An estimated 339 million people worldwide have asthma1, but a lack of stratifying diagnostics means that current guidelines advocate a ‘trial and error’ approach, which results in increased healthcare costs, prolonged periods of poor disease control, and an increased risk of exacerbations. Breath analysis offers the possibility of a rapid, straightforward and non-invasive method to stratify patients2 into receiving the right therapy and monitor what dosage they need.

Asthma management is focused on achieving control of symptoms to minimize the risk of future exacerbations. Many patients do not respond sufficiently to treatment, however, so their symptoms are not kept adequately under control. In the UK, 4.4% of patients fail to respond to standard therapies even at high doses, and account for more than half of asthma costs to the NHS.

Precision Medicine for Asthma

The treatment of asthma can be challenging because the condition consists of a number of complex, overlapping, phenotypes (Figure 1, top row) with similar symptoms, but which require different treatments.

Precision Medicine for Asthma
Figure 1. Precision Medicine for Asthma. Asthma management is challenging due to multiple phenotypes, inflammatory subtypes and endotypes with different underlying molecular mechanisms or responses to treatment. Metabolomics is being explored as a route to discover biomarkers to identify disease endotypes or treatable traits, enabling a precision medicine approach to asthma treatment.

Chronic airway inflammation has diverse origins and triggers, and can be broken down into a range of different subtypes of pulmonary inflammation. These inflammatory subtypes (Figure 1, second row) can be further divided into different endotypes, with different underlying molecular mechanisms or responses to treatment.

There is now a considerable move towards precision medicine in asthma, as highlighted by Dr Stephen Fowler at the 2018 Breath Biopsy Conference and in the Lancet Respiratory Asthma Task Force and others3,4. By identifying different disease endotypes or treatable traits, precision medicine addresses asthma’s underlying heterogeneity, enabling the right treatment to be given to the right patient at the right time.

The last decade has seen the approval of biological drugs such as XOLAIR®, NUCALA®, CINQAIR®, FASENRA®, and DUPIXENT® targeted at specific pathways relevant to inflammatory subtypes, yet their approval for clinical use has been delayed due to the high cost of the treatment, combined with the difficulty of identifying patients with the correct asthma phenotype who would benefit from the drug.

Volatile Metabolites - Biomarkers for Precision Medicine

Differences in the metabolic profile of individuals with asthma compared to healthy controls have already been detected in serum - even in steroid naïve patients with mild asthma5. The differences shown in this case relate both to the severity of the disease, and also to the steroid treatment.

An increasing body of evidence shows that volatile metabolites in exhaled breath are promising biomarkers that relate to metabolic changes caused by inflammation of the airways6.

A systematic review with meta-analysis and recent prospective studies favored exhaled volatile organic compounds as one of the most promising biomarkers in asthma diagnosis and monitoring.6

Breath Biopsy® enables you to analyze volatile metabolites in exhaled breath, providing a new non-invasive approach to characterize different disease endotypes.

Breath Biomarkers for Asthma

One breath-based biomarker, fractional exhaled nitric oxide (FENO), is already being used to support asthma diagnosis. FENO reflects a protective biochemical pathway of the lungs, but lacks specificity, as it is a single biomarker affected by many processes other than asthma.

Studies have demonstrated that volatile organic compounds (VOCs) in exhaled breath can outperform FENO and lung function tests as biomarkers when discriminating between asthmatics and healthy controls7. It has also been shown that VOCs can be used to discriminate with a high degree of accuracy between asthmatic children and those with transient wheezing8.

Discrimination of Asthmatic vs. Non-Asthmatic Patients with Breath Biopsy®

We’ve examined the ability of VOCs analyzed using our Breath Biopsy platform to discriminate between asthmatic and non-asthmatic patients (Figure 2). As you can see, even in a heterogeneous clinical trial population, which included individuals with a wide variety of pulmonary conditions, the VOC profile discriminates well between patients with or without a diagnosis of asthma.

Discriminating between asthmatics and non-asthmatics using Breath Biopsy
Figure 2. Breath VOCs analyzed using Owlstone Medical’s Breath Biopsy platform were used to build a classifier which could discriminate between patients with or without a diagnosis of asthma. The Receiver Operator Characteristics (ROC) curve shows an area under the curve of 0.92. The ROC evaluates the ability of a test to discriminate between states with 1.0 indicating a perfect test. The patient population included individuals with a wide variety of pulmonary conditions, participating in a larger clinical trial.

Distinguishing Inflammatory Subtypes in Asthma

There is evidence that breath VOCs can be used to classify patients by asthma phenotype with high accuracy. For example Ibrahim et al.9 provide evidence that VOCs in breath correlate with different inflammatory subtypes in asthma, as defined by sputum cell counts, while Schleich et al.2 used VOCs to develop high accuracy predictive tests to stratify patients based on these subtypes.

VOC biomarkers in breath could therefore make it possible to distinguish different phenotypes of asthma as defined by inflammatory responses. This could enable more patients to get the most effective treatments sooner and with less need for trial and error.

Learn more about VOC biomarkers and their application in asthma treatment stratification

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Breath Biopsy for Distinguishing Controlled vs. Uncontrolled Asthma

Reliable biomarkers to identify patients with uncontrolled asthma, or to predict exacerbations, would inform treatment decisions and facilitate disease management.

The profile of VOCs in exhaled breath can be used to distinguish between patients with controlled and uncontrolled asthma (Figure 3), which is an important aspect of a patient’s asthma phenotype.

Distuinguishing controlled and uncontrolled asthma with Breath Biopsy
Figure 3. Breath VOCs analyzed using Owlstone Medical’s Breath Biopsy platform were used to build a classifier which could identify individuals with self-reported uncontrolled asthma with 85% sensitivity and 98% specificity. The Receiver Operator Characteristics (ROC) curve shows an area under the curve of 0.88. A subpopulation of individuals participating in a larger clinical trial were included in this analysis.

It has also been reported that breath VOCs analysed using our FAIMS technology can potentially predict loss of control in asthma10. In this study the Lonestar VOC Analyzer, was shown to outperform sensor array type eNoses and gas chromatography-mass spectrometry (GC-MS). 

VOCs for Treatment Stratification

A reliable tool to identify whether the patient is likely to respond to a particular treatment would be an important development.

Predicting Steroid Responsiveness

Van der Schee et al. that found that VOCs in breath are able to predict responsiveness to steroid treatment in steroid-naïve, mild to moderate asthma patients11. With an area under the curve of 0.88, VOCs outperformed both FENO and measurements of eosinophil cells from sputum samples.

Breath VOCs Differentiate Treatment Groups

Promising initial results from the U-BIOPRED (Unbiased BIOmarkers in PREDiction of respiratory disease outcomes) consortium project show that VOCs measured using a Lonestar VOC Analyzer could be used to stratify asthmatic patients into treatment subgroups. For example, VOCs discriminated between anti-IgE-treated XOLAIR and non-treated severe asthma patients with 83% accuracy12,13.

Asthma treatment stratification

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Chronic Obstructive Pulmonary Disease (COPD)

COPD refers to a group of diseases that cause airflow blockage and breathing-related problems. The Global Burden of Disease Study (2016) reported 251 million cases of COPD globally and contributes to around 5% of deaths (2015, 3.17 million)14, by the end of 2020 it is anticipated to be the third leading cause of death worldwide15. COPD is usually progressive, and exacerbations, which are typically related to viral or bacterial infections, are a major cause of lung function decline. Cigarette smoking is the most commonly encountered risk factor for COPD.

Asthma and COPD are both chronic inflammatory lung diseases that cause airflow limitation by bronchoconstriction. As such, they have many similarities but also important differences. Often, the nature of the inflammation present differs; in asthma the inflammation is commonly eosinophilic, whereas in COPD it is predominantly neutrophilic16. That said, there is significant overlap between the conditions, with multiple subgroups of patients with distinct clinical and pathophysiological features17.

As with asthma, COPD symptoms can arise from multiple mechanisms, so finding the most suitable treatments for each patient can be challenging. Hence, there has been an increasing call in recent years for exploring precision medicine approaches to COPD and a growing amount of research is going into developing tailored biological treatments for COPD18.

VOCs and COPD

As for asthma, breath VOCs could be a useful tool in the diagnosis of COPD. In a study of 28 COPD patients, VOCs in exhaled breath were measured with both GC-MS and also electronic nose devices: a composite of 19 VOCs were found to be highly associated with eosinophil cationic protein (ECP) – a known biomarker of eosinophil activity – while another 4 were highly associated with myeloperoxidase (MPO) – an activity marker for neutrophilic cells (Figure 4)19. Analysis showed high sensitivity and specificity (AUC 1.00 for ECP, 0.96 for MPO) for the 12 mild COPD patients but not for 16 moderate COPD patients: since mild COPD is more commonly typified by airways inflammation while moderate COPD is less associated with inflammation and more associated with airway remodeling, this suggests that these VOCs may be used for measuring activity in airway inflammation.

VOCs COPD inflammatory markers
Figure 4. Identifying links between VOCs in breath and inflammatory biomarkers in different forms of COPD. ECP is a marker of activated eosinophils while MPO indicates neutrophil activity.

Using Breath Biopsy to distinguish between patients with COPD and lung cancer

Evidence suggests that breath VOCs collected and analysed using the Breath Biopsy platform can be used to differentiate between COPD and other lung diseases. Figure 5 shows the performance of the platform in a population of 227 COPD patients and 269 lung cancer patients. Breath Biopsy could distinguish lung cancer patients from those with COPD with a sensitivity of 91% and a specificity of 64%. The area under the receiver operator curve equals 0.80 ± 0.03.

Differentiating between lung cancer and COPD
Figure 5. Results from Owlstone Medical's Breath Biopsy platform showing the ability to use exhaled VOC analysis to differentiate between lung cancer and COPD. Sensitivity 91%, Specificity 64%, ROC 0.80.

Summary

Promising results indicate that VOCs in exhaled breath reflect specific molecular processes that underlie chronic inflammation in asthma and COPD, making them ideal biomarkers for precision medicine and treatment stratification.

By enabling the non-invasive collection and analysis of (VOCs) in exhaled breath, Breath Biopsy provides a new approach to discover biomarkers that could characterize different disease endotypes and predict the effectiveness of treatment.

References

  1. The Global Asthma Report, The Global Asthma Network (2018). http://www.globalasthmareport.org/index.html
  2. Schleich et al., Exhaled Volatile Organic Compounds are Able to Discriminate between Neutrophilic and Eosinophilic Asthma, Am J Respir Crit Care Med, (2019). doi.org/10.1164/rccm.201811-2210OC
  3. Pavord et al., After asthma: redefining airways diseases, The Lancet, (2017). dx.doi.org/10.1016/S0140-6736(17)30879-6
  4. Chung, Personalised medicine in asthma: time for action,  Eur. Resp. Rev., 26, (2017).   dx.doi.org/10.1183/16000617.0064-2017
  5. Reinke et al., Metabolomics analysis identifies different metabotypes of asthma severity, Eur. Resp. J., 49, (2017). dx.doi.org/10.1183/13993003.01740-2016
  6. Pité et al., Metabolomics in asthma: where do we stand?, Curr. Opin. Pulm. Med. (2017).  dx.doi.org/10.1097/MCP.0000000000000437
  7. Montuschi et al., Diagnostic performance of an electronic nose, fractional exhaled nitric oxide, and lung function testing in asthma, Chest. 137 (2010) 790–796. dx.doi.org/10.1378/chest.09-1836
  8. Dallinga et al., Volatile organic compounds in exhaled breath as a diagnostic tool for asthma in children., Clin. Exp. Allergy., 40 (2010) 68–76. dx.doi.org/10.1111/j.1365-2222.2009.03343.x
  9. Ibrahim et al., Non-invasive phenotyping using exhaled volatile organic compounds in asthma., Thorax, 66 (2011) 804–809. dx.doi.org/10.1136/thx.2010.156695
  10. Brinkman et al., Exhaled breath profiles in the monitoring of loss of control and clinical recovery in asthma, Clin. Exp. Allergy, (2017), dx.doi.org/10.1111/cea.12965
  11. van der Schee et al., Predicting steroid responsiveness in patients with asthma using exhaled breath profiling, Clin. Exp. Allergy. 43 (2013) 1217–1225. dx.doi.org/10.1111/cea.12147
  12. Santini et al., Discrimination between oral corticosteroid-treated and oral corticosteroid-non-treated severe asthma patients by an electronic nose platform, Eur. Respir. J. 44 (2014). erj.ersjournals.com/content/44/Suppl_58/P2054
  13. Santini et al., Breathomics can discriminate between anti IgE-treated and non-treated severe asthma adults, Eur. Respir. J. 46 (2015). http://erj.ersjournals.com/content/46/suppl_59/OA1463
  14. World Health Organization, COPD Fact Sheet (2017). https://www.who.int/news-room/fact-sheets/detail/chronic-obstructive-pulmonary-disease-(copd)
  15. Global Strategy for Prevention, Diagnosis and Management of COPD, Global Initiative for Chronic Obstructive Lung Disease (2019) https://goldcopd.org/gold-reports/
  16. Buist, Similarities and differences between asthma and chronic obstructive pulmonary disease: treatment and early outcomes, Eur. Respir. J. (2003). dx.doi.org/10.1183/09031936.03.00404903
  17. Kolsum et al., Clinical characteristics of eosinophilic COPD versus COPD patients with a history of asthma, Respir. Res. (2017). doi.org/10.1186/s12931-017-0559-0
  18. Pavord, Biologics and chronic obstructive pulmonary disease, J. Allergy Clin. Immunol. (2019). doi.org/10.1016/j.jaci.2018.04.020 
  19. Fens et al., Exhaled air molecular profiling in relation to inflammatory subtype and activity in COPD, Eur. Respir. J. (2011), 38(6):1301 – 1309. dx.doi.org/10.1183/09031936.00032911