VOC biomarkers offer a route to more effective personalised asthma treatment

An estimated 334 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 patients into receiving the right therapy and monitor what dosage they need.

Asthma is an inflammatory disease of the airways. It is characterised by symptoms including wheezing, coughing, chest tightness, and shortness of breath. 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.

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.

VOC biomarkers for asthma

Breath based biomarkers offer a non-invasive route for asthma diagnosis and patient stratification. Biomarker FENO (fractional exhaled nitric oxide) is linked to airway inflammation and is already being used to support asthma diagnosis. FENO is useful, but as a single biomarker affected by many processes other than asthma, it lacks specificity.

Existing evidence suggests that other volatile organic compounds (VOCs) in breath are also strongly affected by the inflammation that characterizes asthma. Studies have demonstrated that VOC biomarkers can outperform FENO and lung function tests when discriminating between asthmatics and healthy controls2. 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 wheezing3.

Study shows FAIMS outperforms eNose and GC-MS at predicting loss of control in asthma

Owlstone Medical’s field asymmetric ion mobility spectrometer (FAIMS), the Lonestar VOC Analyzer, has been shown to outperform sensor array type eNoses and gas chromatography-mass spectrometry (GC-MS) at predicting loss of control in patients with mild-to-moderate persistent asthma. A pilot study by Brinkman et al.4 published in the journal Clinical and Experimental Allergy found that VOC breath profiles measured with the FAIMS platform could be used to distinguish when patients were suffering loss of control vs. baseline with 95% accuracy. The technique could also be used to correctly classify between the loss of control and subsequent recovery with 86% accuracy.

The authors noted that FAIMS was able to distinguish between the baseline, loss of control and recovery more accurately than GC-MS (68 - 77% accuracy) and sensor-type eNoses also tested in the study.

Results of Asthma pilot study
Figure 1. Breath VOC profiles measured using FAIMS showed 95% correct classification for baseline vs. loss of control and 86% for loss of control vs. recovery4.


Evidence FAIMS can diagnose asthma

There are promising initial results from Owlstone Medical’s NHS funded LuCID clinical trial, which uses the ReCIVA Breath Sampler and Lonestar VOC Analyzer to analyze VOCs in patient breath samples.

ROC Lucid Asthma
Figure 2. Discriminating patients with asthma in LuCID clinical trial population. AUC 0.92.

Data collected so far indicates that GC-MS combined with FAIMS can discriminate between asthmatic and non-asthmatic patients (AUC 0.92, Figure 2) in a cohort of patients under clinical suspicion of lung cancer (a heterogeneous population with a wide variety of medical conditions). Such an approach allows identification of disease specific volatiles greatly facilitating translation to clinical practice.

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VOCs for personalised medicine and treatment stratification

Asthma symptoms are caused by chronic inflammation in the small airways. Many different underlying mechanisms are responsible for this inflammation, with different treatments required for different inflammation types. At present there is no single diagnostic test for asthma in part because of its heterogeneous underlying pathophysiology.

The difference in cell activity related to different inflammatory subtypes of asthma is reflected by the metabolites these cells produce, and consequently by the VOCs in exhaled breath.

Treatment success is dependent on correctly identifying asthma inflammatory subtype

While the diagnostic power of breath VOCs could provide a valuable new tool for clinicians, a more impactful application of an asthma Breath Biopsy® is likely to be in the phenotyping of the disease by characterization of underlying inflammation.

There is evidence that VOCs can be used to classify patients by asthma phenotype with high accuracy5. VOCs will therefore allow different phenotypes of asthma defined by different inflammatory responses to be distinguished. There is also further evidence that VOCs outperform FENO or measurements of eosinophil cells from coughed up sputum samples when predicting steroid responsiveness in mild to moderate asthma sufferers5.

These results clearly points towards the use of Breath Biopsy® as a non-invasive companion diagnostic for therapy stratification, which could be used to personalize treatment to a specific asthma phenotype.

This would be an important development as the last decade has seen the approval of biological drugs such as XOLAIR® 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.

Using biomarkers to characterize asthma types has so far not found widespread adoption due to the invasive nature of existing cell harvesting techniques such as bronchoalveolar lavage, and the limited applicability of FENO testing at identifying responders to new targeted biologic treatments aimed at patients.

VOCs measured using FAIMS discriminated between anti-IgE-treated XOLAIR and non-treated severe asthma patients with 83% accuracy

Promising initial results from the U-BIOPRED (Unbiased BIOmarkers in PREDiction of respiratory disease outcomes) consortium project show that VOCs measured using a FAIMS device could be used to stratify asthmatic patients into treatment sub-groups. For example, VOCs discriminated between anti-IgE-treated XOLAIR and non-treated severe asthma patients with 83% accuracy7,8.

The small form factor and proven accuracy differentiates FAIMS from current alternatives as the only technology meeting all the requirements for implementation as an asthma stratification tool for general practitioners and pulmonary specialists.

STRATA Clinical Trial

In the STRATA (Stratification of Asthma Treatment by Breath Analysis) programme, Owlstone Medical seeks to replace the trial and error approach for asthma treatment selection, and use our Breath Biopsy® platform to stratify asthma patients and match them to the correct existing treatments first time. As a result, we will bring lasting benefit to patients, minimize costs for the NHS and make a positive impact on the annual toll of 54,000 asthma-related emergency hospital admissions and 1,167 asthma-related deaths.



  1. The Global Asthma Report, (2014).
  2. Montuschi et al., Diagnostic performance of an electronic nose, fractional exhaled nitric oxide, and lung function testing in asthma, Chest. 137 (2010) 790–796.
  3. Dallinga et al., Volatile organic compounds in exhaled breath as a diagnostic tool for asthma in children., Clin. Exp. Allergy. 40 (2010) 68–76.
  4. Brinkman et al., Exhaled breath profiles in the monitoring of loss of control and clinical recovery in asthma, Clin. Exp. Allergy, (2017),
  5. Ibrahim et al., Non-invasive phenotyping using exhaled volatile organic compounds in asthma., Thorax. 66 (2011) 804–809.
  6. van der Schee et al., Predicting steroid responsiveness in patients with asthma using exhaled breath profiling, Clin. Exp. Allergy. 43 (2013) 1217–1225.
  7. 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).
  8. Santini et al., Breathomics can discriminate between anti IgE-treated and non-treated severe asthma adults, Eur. Respir. J. 46 (2015).