Inflammatory Bowel Disease

The pathogenesis of IBD involves bacteria, which ferment non-starch polysaccharides in the colon producing a fermentation profile that through altered gut permeability can be traced from VOCs

Inflammatory Bowel Disease

Inflammatory bowel disease (IBD) is a group of autoimmune diseases primarily affecting the colon and small intestine. The principal types of IBD are Crohn’s disease (CD) and ulcerative colitis (UC). IBD is common, and affects approximately 1 - 1.3 million people in the US1.

The cause of IBD is not entirely understood, but it is widely believed to be the result of complex interactions between an individual’s genetic susceptibility, environmental triggers (e.g. diet, lifestyle, etc.) and the influence of an individual’s gastrointestinal bacterial colonies.

At present the diagnosis of IBD and the differentiation of disease types takes a multi-modal approach that includes clinical, histological, serological, radiological and endoscopic observations2.

Accurate disease stratification is vital for determining the best treatment strategy, but at present 10 - 15% of patients elude correct categorization. Accurate phenotyping often requires endoscopy of the intestine, which is high cost, uncomfortable, has high non-compliance rates and can result in complications such as perforation of the bowel3,4.

Metabolic VOC biomarkers offer a non-invasive route to the accurate stratification of IBD patients. They also offer a potential means of determining which patients will develop more severe disease phenotypes, and who will benefit most from expensive biological and/or immunomodulating agents5,6.

Breath Biopsy® for IBD diagnosis and stratification

To determine whether breath VOCs offer an effective route to diagnosis and stratification of patients with IBD, researchers have used Owlstone Medical’s Lonestar VOC Analyzer which uses  FAIMS technology to see if patients’ breath VOC profile can be used to distinguish IBD patients from healthy controls, and to also distinguish those with Crohn’s disease (CD) and ulcerative colitis (UC)7. IBD-related alterations to the gut permeability can result in markers originating in the gastrointestinal tract appearing elsewhere in the body.  This can lead to elevated levels of IBD-related VOC biomarkers in exhaled breath.

A total of 76 subjects were recruited for the study, 54 of which had histologically confirmed IBD (29 UC and 25 CD) as well as 22 healthy controls. The predictive performance of the data from FAIMS analysis of exhaled breath samples was studied using a pipeline consisting of wavelet transformation, feature selection and a sparse logistic regression classifier. This was used to classify samples and calculate sensitivities and specificities as part of a 10-fold cross-validation.

The box plot (Figure 1) shows the predictive power of IBD (UC and CD) vs. controls, UC vs. controls, CD vs. controls and finally UC vs. CD.

FAIMS predictive power

inflammatory bowel disease box plot

Figure 1. Predictions of classifier to different combinations of diseases and controls (UC – ulcerative colitis, CD – Crohn’s disease, V – volunteer (healthy control)). The study used the Lonestar VOC Analyzer (FAIMS) to analyze VOC biomarkers in breath7.

The analysis showed that patients with IBD could be distinguished from control patients using FAIMS analysis of VOCs in breath samples with a sensitivity of 74% (95% confidence intervals (CI): 0.65–0.82) and specificity of 75% (95% CI: 0.53–0.90), p-value 6.2 × 10−7. The AUC (area under curve) was 0.82 (95% CI: 0.74-0.89) (Figure 2).

FAIMS could distinguish those with UC from those with CD with a sensitivity of 67% (95% CI:0.54–0.79) and specificity of 67% (95% CI: 0.54–0.79), p-value 9.23 × 10−4. The AUC was 0.70 (95% CI: 0.60–0.80).

Inflammatory bowel disease ROC
Figure 2. Receiver operator curve (ROC) plot of IBD (UC and CD) vs. healthy controls.The study used the Lonestar VOC Analyzer (FAIMS) to analyze VOC biomarkers in breath7.

This study confirms the utility of FAIMS exhaled VOC analysis to distinguish IBD from healthy controls, and UC from CD. It conforms to other studies using different technology, whilst affirming exhaled VOCs as biomarkers for diagnosing IBD.


FAIMS stool analysis for pediatric IBD diagnosis and monitoring

Endoscopic procedures for the diagnosis of IBD carry a particularly high burden for pediatric patients. Typically, this group requires hospitalization for intensive bowel preparation by nasogastric tube and general anaesthesia whilst the endoscopy is performed.

Existing biomarkers used in the diagnosis and monitoring of IBD disease activity (including C-reactive protein, erythrocyte sedimentation rate, fecal calprotectin and lactoferrin) are characterized by relatively low specificity, especially in children.

Fecal VOCs reflect alterations of both gut microbiota and human metabolism, and therefore offer an alternative source of biomarkers for IBD diagnosis and monitoring. Another recent study8 has used Owlstone Medical’s ATLAS Headspace Sampler and Lonestar VOC Analyzer (FAIMS) to observe VOC biomarkers in stool samples to aid in the diagnosis of pediatric IBD patients.

It was observed that fecal VOC analysis by FAIMS could discriminate pediatric de novo IBD patients from healthy controls (Figure 3). It was found that VOCs measured using FAIMS had a high specificity compared to fecal calprotectin.

Discriminating between pediatric patients with Crohn's disease and controls with fecal VOCs
Figure 3.Box plots for the best classification result for Crohn’s disease vs healthy controls. AUC (95%CI) 0.90 ± 0.10, sensitivity 83%, specificity 83%8.

The authors note that the method has the potential to serve as a complementary, non-invasive technique in the diagnosis of pediatric IBD, that could limit the number of endoscopies needed in a subset of children with suspected IBD.



  1. CDC - Epidemiology of the IBD - Inflammatory Bowel Disease, (n.d.).
  2. Kurada et al., Review article: breath analysis in inflammatory bowel diseases, Aliment. Pharmacol. & Ther. 41 (2015) 329–341.
  3. Blotière et al., Perforations and haemorrhages after colonoscopy in 2010: a study based on comprehensive French health insurance data (SNIIRAM)., Clin. Res. Hepatol. Gastroenterol. 38 (2014) 112–117.
  4. Friedman et al., Factors that affect adherence to surveillance colonoscopy in patients with inflammatory bowel disease., Inflamm. Bowel Dis. 19 (2013) 534–539.
  5. Devlin et al., Evolving Inflammatory Bowel Disease Treatment Paradigms: Top-Down Versus Step-Up, Med. Clin. North Am. 94 (2010) 1–18.
  6. Yoshida et al., Diagnosis of gastroenterological diseases by metabolome analysis using gas chromatography–mass spectrometry, J. Gastroenterol. 47 (2012) 9–20.
  7. Arasaradnam et al., Non-invasive exhaled volatile organic biomarker analysis to detect inflammatory bowel disease (IBD)., Dig. Liver Dis. 48 (2016) 148–153. Download paper.
  8. van Gaal et al., Faecal volatile organic compounds analysis using field asymmetric ion mobility spectrometry: non-invasive diagnostics in paediatric inflammatory bowel disease, J. Breath Res., 2017, in press. Download paper

We have been using FAIMS for almost five years and have found it able to non-invasively detect a broad range of diseases, including cancer, with high sensitivity and specificity

Professor James Covington
University of Warwick

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