Inflamm Bowel Dis. 2021 Nov 10;izab256. doi: 10.1093/ibd/izab256. Online ahead of print.

Jasmijn Z Jagt ¹, Eduard A Struys ², Ibrahim Ayada ¹, Abdellatif Bakkali ², Erwin E W Jansen ², Jürgen Claesen ³, Johan E van Limbergen ⁴, Marc A Benninga ⁴, Nanne K H de Boer ⁵, Tim G J de Meij ^1 4

Author information

¹Department of Pediatric Gastroenterology, Emma Children's Hospital, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands.

²Department of Clinical Chemistry, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands.

³Department of Epidemiology and Data Science, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands.

⁴Department of Pediatric Gastroenterology, Emma Children's Hospital, Amsterdam UMC, Academic Medical Centre, 1105 AZ Amsterdam, The Netherlands.

⁵Department of Gastroenterology and Hepatology, Amsterdam Gastroenterology and Metabolism Research Institute, Amsterdam UMC, Vrije universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands.

Abstract

Background: Fecal metabolomic profiles differ between pediatric inflammatory bowel disease (IBD) patients and controls and may provide new insights in the pathophysiology of IBD. The role of amino acids, however, is not fully elucidated. We aimed to assess fecal amino acid profiles in pediatric IBD.

Methods: In this case-control study, treatment-naïve, newly diagnosed pediatric IBD patients and a non-IBD control group, matched based on sex and age, were included in 2 tertiary centres. Fecal amino acid profiles were assessed using a targeted high-performance liquid chromatography technique. A random forest classifier method was used to develop a prediction model differentiating IBD from controls and predicting IBD phenotype. The association between IBD localization and amino acid concentrations was tested with ordinal regression models.

Results: We included 78 newly diagnosed IBD patients (40 Crohn's disease [CD], 38 ulcerative colitis [UC]) and 105 controls. Patients with IBD could be differentiated from controls with an accuracy of 82% (sensitivity 63%, specificity 97%). Twenty-nine out of the 42 measured unique amino acids were included in the prediction model. Increased levels of tryptophan, taurine, alanine, ornithine, valine, histidine, and leucine were the most differentiating features. Children with CD and UC could be differentiated from the controls with an accuracy of 80% and 90%, respectively. Inflammatory bowel disease phenotype could not be predicted. Tryptophan, valine, and histidine levels were positively associated with more extended disease in UC patients (P < .05).

Conclusions: Fecal amino acids may enhance understanding of the role of host-microbial interactions in the pathophysiology of IBD and may evolve into biomarkers for pediatric IBD diagnostic and personalized medicine.