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Differentiating coeliac disease from irritable bowel syndrome by urinary volatile organic compound analysis--a pilot study.

Arasaradnam RP, Westenbrink E, McFarlane MJ, Harbord R, Chambers S, O'Connell N, Bailey C, Nwokolo CU, Bardhan KD, Savage R, Covington JA - PLoS ONE (2014)

Bottom Line: GCMS showed a unique peak at 4'67 found only in CD, not D-IBS, which correlated with the compound 1,3,5,7 cyclooctatetraene.This study suggests that FAIMS offers a novel, non-invasive approach to identify those with possible CD, and distinguishes from D-IBS.The presence of cyclooctatetraene in CD specimens will need further validation.

View Article: PubMed Central - PubMed

Affiliation: Clinical Sciences Research Institute, University of Warwick, Coventry, Warwickshire, United Kingdom; Department of Gastroenterology, University Hospital Coventry & Warwickshire, Coventry, Warwickshire, United Kingdom.

ABSTRACT
Coeliac disease (CD), a T-cell-mediated gluten sensitive enteropathy, affects ∼ 1% of the UK population and can present with wide ranging clinical features, often being mistaken for Irritable Bowel Syndrome (IBS). Heightened clinical awareness and serological screening identifies those with potential coeliac disease; the diagnosis is confirmed with duodenal biopsies, and symptom improvement with a gluten-free diet. Limitations to diagnosis are false negative serology and reluctance to undergo biopsy. The gut microbiome is altered in several gastrointestinal disorders, causing altered gut fermentation patterns recognisable by volatile organic compounds (VOC) analysis in urine, breath and faeces. We aimed to determine if CD alters the urinary VOC pattern, distinguishing it from IBS. 47 patients were recruited, 27 with established CD, on gluten free diets, and 20 with diarrhoea-predominant IBS (D-IBS). Collected urine was stored frozen in 10 ml aliquots. For assay, the specimens were heated to 40 ± 0.1°C and the headspace analysed by Field Asymmetric Ion Mobility Spectrometry (FAIMS). Machine learning algorithms were used for statistical evaluation. Samples were also analysed using Gas chromatography and mass spectroscopy (GC-MS). Sparse logistic regression showed that FAIMS distinguishes VOCs in CD vs D-IBS with ROC curve AUC of 0.91 (0.83-0.99), sensitivity and specificity of 85% respectively. GCMS showed a unique peak at 4'67 found only in CD, not D-IBS, which correlated with the compound 1,3,5,7 cyclooctatetraene. This study suggests that FAIMS offers a novel, non-invasive approach to identify those with possible CD, and distinguishes from D-IBS. It offers the potential for monitoring compliance with a gluten-free diet at home. The presence of cyclooctatetraene in CD specimens will need further validation.

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Scatter plot of TTG serology vs classification probability for Coeliac cases.The classification probabilities are the probability of a given patient having Coeliac disease, as determined by the sparse logistic regression algorithm. The overall correlation of these points is 0.28. One outlying point with TTG>60 kU/L has been removed.
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pone-0107312-g003: Scatter plot of TTG serology vs classification probability for Coeliac cases.The classification probabilities are the probability of a given patient having Coeliac disease, as determined by the sparse logistic regression algorithm. The overall correlation of these points is 0.28. One outlying point with TTG>60 kU/L has been removed.

Mentions: Table 5 and Figure 3 show comparisons between the classification probabilities and (respectively) Marsh score, and TTG serology. As can be seen, within this data set there are no strong relationships between the probability of having coeliac (as determined by sparse logistic regression) and either Marsh score or TTG serology.


Differentiating coeliac disease from irritable bowel syndrome by urinary volatile organic compound analysis--a pilot study.

Arasaradnam RP, Westenbrink E, McFarlane MJ, Harbord R, Chambers S, O'Connell N, Bailey C, Nwokolo CU, Bardhan KD, Savage R, Covington JA - PLoS ONE (2014)

Scatter plot of TTG serology vs classification probability for Coeliac cases.The classification probabilities are the probability of a given patient having Coeliac disease, as determined by the sparse logistic regression algorithm. The overall correlation of these points is 0.28. One outlying point with TTG>60 kU/L has been removed.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4199520&req=5

pone-0107312-g003: Scatter plot of TTG serology vs classification probability for Coeliac cases.The classification probabilities are the probability of a given patient having Coeliac disease, as determined by the sparse logistic regression algorithm. The overall correlation of these points is 0.28. One outlying point with TTG>60 kU/L has been removed.
Mentions: Table 5 and Figure 3 show comparisons between the classification probabilities and (respectively) Marsh score, and TTG serology. As can be seen, within this data set there are no strong relationships between the probability of having coeliac (as determined by sparse logistic regression) and either Marsh score or TTG serology.

Bottom Line: GCMS showed a unique peak at 4'67 found only in CD, not D-IBS, which correlated with the compound 1,3,5,7 cyclooctatetraene.This study suggests that FAIMS offers a novel, non-invasive approach to identify those with possible CD, and distinguishes from D-IBS.The presence of cyclooctatetraene in CD specimens will need further validation.

View Article: PubMed Central - PubMed

Affiliation: Clinical Sciences Research Institute, University of Warwick, Coventry, Warwickshire, United Kingdom; Department of Gastroenterology, University Hospital Coventry & Warwickshire, Coventry, Warwickshire, United Kingdom.

ABSTRACT
Coeliac disease (CD), a T-cell-mediated gluten sensitive enteropathy, affects ∼ 1% of the UK population and can present with wide ranging clinical features, often being mistaken for Irritable Bowel Syndrome (IBS). Heightened clinical awareness and serological screening identifies those with potential coeliac disease; the diagnosis is confirmed with duodenal biopsies, and symptom improvement with a gluten-free diet. Limitations to diagnosis are false negative serology and reluctance to undergo biopsy. The gut microbiome is altered in several gastrointestinal disorders, causing altered gut fermentation patterns recognisable by volatile organic compounds (VOC) analysis in urine, breath and faeces. We aimed to determine if CD alters the urinary VOC pattern, distinguishing it from IBS. 47 patients were recruited, 27 with established CD, on gluten free diets, and 20 with diarrhoea-predominant IBS (D-IBS). Collected urine was stored frozen in 10 ml aliquots. For assay, the specimens were heated to 40 ± 0.1°C and the headspace analysed by Field Asymmetric Ion Mobility Spectrometry (FAIMS). Machine learning algorithms were used for statistical evaluation. Samples were also analysed using Gas chromatography and mass spectroscopy (GC-MS). Sparse logistic regression showed that FAIMS distinguishes VOCs in CD vs D-IBS with ROC curve AUC of 0.91 (0.83-0.99), sensitivity and specificity of 85% respectively. GCMS showed a unique peak at 4'67 found only in CD, not D-IBS, which correlated with the compound 1,3,5,7 cyclooctatetraene. This study suggests that FAIMS offers a novel, non-invasive approach to identify those with possible CD, and distinguishes from D-IBS. It offers the potential for monitoring compliance with a gluten-free diet at home. The presence of cyclooctatetraene in CD specimens will need further validation.

Show MeSH
Related in: MedlinePlus