Differences in amino acid and lipid metabolism distinguish Crohn's from idiopathic/cryptoglandular perianal fistulas by tissue metabonomic profiling and may offer clues to underlying pathogenesis.

Abstract

Few studies have investigated perianal fistula etiopathogenesis, and although the cryptoglandular theory is widely accepted in idiopathic cases, in Crohn's disease, it is thought to involve the interplay between microbiological, immunological and genetic factors. A pilot study was conducted to assess for metabolic variations in Crohn's perianal fistula tissue that might differ from that of idiopathic (cryptoglandular) perianal fistula tissue as a comparator. The goal was to identify any potential biomarkers of disease, which may improve the understanding of pathogenesis. Fistula tract biopsies were obtained from 30 patients with idiopathic perianal fistula and 20 patients with Crohn's anal fistula. Two different assays were used in an ultra-high-performance liquid chromatography system coupled with a mass spectrometric detector to achieve broad metabolome coverage. Univariate and multivariate statistical data analyses were used to identify differentiating metabolic features corresponding to the perianal fistula phenotype (i.e. Crohn's disease vs. idiopathic). Significant orthogonal partial least squares discriminant analysis predictive models (validated with cross-validated-analysis of variance P value <0.05) differentiated metabolites from tissue samples from Crohn's vs. idiopathic anal fistula patients using both metabolic profiling platforms. A total of 41 metabolites were identified, suggesting alterations in pathways, including amino acid, carnitine and lipid metabolism. Metabonomics may reveal biomarkers of Crohn's perianal fistula. Further work in larger numbers is required to validate the findings of these studies as well as cross-correlation with microbiome work to better understand the impact of host-gut/environment interactions in the pathophysiology of Crohn's and idiopathic perianal fistulas and identify novel therapeutic targets.