Fecal gut microbiota and amino acids as noninvasive diagnostic biomarkers of Pediatric inflammatory bowel disease.

BACKGROUND AND AIMS

Fecal calprotectin (FCP) has limited specificity as diagnostic biomarker of pediatric inflammatory bowel disease (IBD), leading to unnecessary invasive endoscopies. This study aimed to develop and validate a fecal microbiota and amino acid (AA)-based diagnostic model.

METHODS

Fecal samples from a discovery cohort ( IBD and healthy controls [HC]) were used to develop the diagnostic model. This model was applied in a validation cohort ( IBD and controls with gastrointestinal symptoms [CGI]). Microbiota and AAs were analyzed using interspace profiling and liquid chromatography-mass spectrometry techniques, respectively. Machine learning techniques were used to build the diagnostic model.

RESULTS

In the discovery cohort (58 IBD, 59 hC), two microbial species ( and ) and four AAs (leucine, ornithine, taurine, and alpha-aminoadipic acid [AAD]) combined allowed for discrimination between both subgroups (AUC 0.94, 95% CI [0.89, 0.98]). In the validation cohort (43 IBD, 38 CGI), this panel of six markers could differentiate patients with IBD from CGI with an AUC of 0.84, 95% CI [0.67, 0.95]). Leucine showed the best diagnostic performance (AUC 0.89, 95% CI [0.81, 0.95]).

CONCLUSIONS

Leucine might serve as adjuvant noninvasive biomarker in the diagnostic work-up of pediatric IBD. Future research should investigate whether the combination of leucine with FCP could improve specificity and may help tailor the course of diagnostics.