Comparison of the metabolomic profiles of irritable bowel syndrome patients with ulcerative colitis patients and healthy controls: new insights into pathophysiology and potential biomarkers

Abstract

Background: Evaluation of the metabolomic profile of patients with irritable bowel syndrome offers an opportunity to identify novel pathophysiological targets and biomarkers that could discriminate this disorder from related conditions. Aim: To identify potential urinary biomarkers that discriminate irritable bowel syndrome patients from ulcerative colitis patients in remission and healthy controls and to explore the pathophysiology of irritable bowel syndrome using a metabolomic approach.Methods: Urine samples were collected from 39 irritable bowel syndrome patients, 53 ulcerative colitis patients in clinical remission and 21 healthy controls. Urinary metabolites were identified and quantified using direct infusion/liquid chromatography tandem mass spectrometry and gas-chromatography mass spectrometry. Results:Patients with irritable bowel syndrome had a unique urinary metabolome that could separate them from ulcerative colitis patients with an area under the curve = 0.99 (95% confidence interval 0.95-1.00). The most important metabolites for this separation were a group of amino acids and organic acids. In addition, subjects with irritable bowel syndrome could be discriminated from healthy controls using their metabolic fingerprints. Irritable bowel syndrome patients had lower urinary Phosphatidyl choline acyl-alkyl C38:6, dopamine and p-hydroxybenzoic acid than healthy controls. Levels of some urinary metabolites including histamine correlated significantly with irritable bowel syndrome symptom severity scores. Conclusions:Irritable bowel syndrome patients have a unique urinary metabolomic profile compared to ulcerative colitis patients in clinical remission or healthy subjects. These data suggest that metabolomic profiling may provide important insights into pathophysiology and testable biomarkers to discriminate irritable bowel syndrome from other disorders that can mimic this condition and can be used to assess its severity and identify potential novel pathophysiological pathways.Stephen Vanner and L. Dieleman contributed equally for this article.

Application of metabolomics to the study of irritable bowel syndrome

“…1 H‐NMR 6,29‐35 and mass spectroscopy (MS) 5,19,27,33,36‐46 are the main detection techniques available that determine the types of metabolites detected. 1 H‐NMR detects all organic classes, is quantitative, and can be used to identify the molecular structure but is more expensive, has relatively lower sensitivity, requires greater sample volumes and cannot detect inorganic ions or salts.…”

“…Understanding the nature and rigor of bioinformatics applied to the data generated in each study is critical to understanding the validity and implications of the findings, but these details are often not fully reported. Table 1 shows that the predominant method is multivariate analysis (see Worley et al 49 for details), but other bioinformatics approaches have also been used 6,19,27,29‐35,38,40,43‐46,50‐52 …”

“…This may be useful in identifying subsets of individuals in an otherwise homogeneous cohort. To date, IBS studies have used HCA in several ways including combining with other analysis (heat maps) to discriminate IBS patients from controls, to monitor the stability of metabolite profiles over time, to discriminate metabolite groups in preclinical IBS models and as a means to better organize the data 9,30,43,44 …”

“…The pruning of models using VIP values is common; however, like the R 2 and Q 2 values, the cut‐off used has not been consistent between IBS studies and is often not reported. Of the 17 studies which performed multivariate analysis, for example, PCA or OPLS‐DA using metabolomic data, 6,19,27,29‐33,35,37,38,40,43‐45,51,52 only 6 identified their R 2 and Q 2 6,19,29,31,35,43,44 while 5 presented their VIP cut‐off value which averaged > 1 6,19,35,37,43,44 . Other modeling tools are also available (such as DModX or Hotelling's 35 ) but reporting is not always clear.…”

“…Metabolomics offer the potential to look for a “metabolic IBS profile” which could provide insights into pathophysiology and/or provide biomarkers for subsets of patients 58 . Although a number of studies have shown metabolomic analyses to differentiate IBS from HC, 26,27,33,36,37,40,41,43‐45,51,59,60 a common metabolic profile has not been identified 30,39,61 (Table 1) 2,33,36,37,39,40,43,44 (Table 2,3). These discrepancies are likely due to multiple factors as previously discussed, but two seem to be particularly important.…”