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

AI Article Synopsis

  • Coeliac disease (CD) affects about 1% of the UK population and is often confused with Irritable Bowel Syndrome (IBS), but can be diagnosed through serology and duodenal biopsies, with symptom improvement on a gluten-free diet.
  • The study explored whether urinary volatile organic compounds (VOCs) could differentiate CD from diarrhea-predominant IBS through advanced analysis techniques like Field Asymmetric Ion Mobility Spectrometry (FAIMS) and Gas Chromatography-Mass Spectrometry (GC-MS).
  • Results showed that FAIMS could effectively distinguish CD from D-IBS with high accuracy, and identified a unique compound in CD samples, suggesting potential for a non-invasive diagnostic method and monitoring for gluten-free diet compliance.

Article 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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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4199520PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0107312PLOS

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