%0 Journal Article
%T Gut metabolome and microbiota signatures predict response to treatment with exclusive enteral nutrition in a prospective study in children with active Crohn's disease.
%A Nichols B
%A Briola A
%A Logan M
%A Havlik J
%A Mascellani A
%A Gkikas K
%A Milling S
%A Ijaz UZ
%A Quince C
%A Svolos V
%A Russell RK
%A Hansen R
%A Gerasimidis K
%J Am J Clin Nutr
%V 119
%N 4
%D 2024 04
%M 38569785
%F 8.472
%R 10.1016/j.ajcnut.2023.12.027
%X Predicting response to exclusive enteral nutrition (EEN) in active Crohn's disease (CD) could lead to therapy personalization and pretreatment optimization.
This study aimed to explore the ability of pretreatment parameters to predict fecal calprotectin (FCal) levels at EEN completion in a prospective study in children with CD.
In children with active CD, clinical parameters, dietary intake, cytokines, inflammation-related blood proteomics, and diet-related metabolites, metabolomics and microbiota in feces, were measured before initiation of 8 wk of EEN. Prediction of FCal levels at EEN completion was performed using machine learning. Data are presented with medians (IQR).
Of 37 patients recruited, 15 responded (FCal < 250 μg/g) to EEN (responders) and 22 did not (nonresponders). Clinical and immunological parameters were not associated with response to EEN. Responders had lesser (μmol/g) butyrate [responders: 13.2 (8.63-18.4) compared with nonresponders: 22.3 (12.0-32.0); P = 0.03], acetate [responders: 49.9 (46.4-68.4) compared with nonresponders: 70.4 (57.0-95.5); P = 0.027], phenylacetate [responders: 0.175 (0.013-0.611) compared with nonresponders: 0.943 (0.438-1.35); P = 0.021], and a higher microbiota richness [315 (269-347) compared with nonresponders: 243 (205-297); P = 0.015] in feces than nonresponders. Responders consumed (portions/1000 kcal/d) more confectionery products [responders: 0.55 (0.38-0.72) compared with nonresponders: 0.19 (0.01-0.38); P = 0.045]. A multicomponent model using fecal parameters, dietary data, and clinical and immunological parameters predicted response to EEN with 78% accuracy (sensitivity: 80%; specificity: 77%; positive predictive value: 71%; negative predictive value: 85%). Higher taxon abundance from Ruminococcaceae, Lachnospiraceae, and Bacteroides and phenylacetate, butyrate, and acetate were the most influential variables in predicting lack of response to EEN.
We identify microbial signals and diet-related metabolites in feces, which could comprise targets for pretreatment optimization and personalized nutritional therapy in pediatric CD.