TY - JOUR
T1 - Gut metabolome and microbiota signatures predict response to treatment with exclusive enteral nutrition in a prospective study in children with active Crohn's disease
AU - Nichols, Ben
AU - Briola, Anny
AU - Logan, Michael
AU - Havlik, Jaroslav
AU - Mascellani, Anna
AU - Gkikas, Konstantinos
AU - Milling, Simon
AU - Ijaz, Umer Zeeshan
AU - Quince, Christopher
AU - Svolos, Vaios
AU - Russell, Richard K.
AU - Hansen, Richard
AU - Gerasimidis, Konstantinos
N1 - Data availability statement: Anonymized data may become available to third parties after request to the corresponding author and for only for those patients who provided written consent for this specific aspect of study participation.
Funding Information: This research received funding from The Glasgow Children’s Hospital Charity, Nestle Health Science and The Leona M. and Harry B. Helmsley Charitable Trust. ML received a studentship by the Engineering and Physical Sciences Research Council (EPSRC) and Nestle Health Science. UZI was funded by Natural Environment Research Council (NERC NE/L011956/1) and supported by EPSRC (EP/P029329/1 and EP/V030515/1). BN was partially funded by the Biotechnology and Biological Sciences Research Council (BB/R006539/1).
PY - 2024/4
Y1 - 2024/4
N2 - Background: Predicting response to exclusive enteral nutrition (EEN) in active Crohn's disease (CD) could lead to therapy personalization and pretreatment optimization. Objectives: 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. Methods: 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). Results: 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. Conclusions: We identify microbial signals and diet-related metabolites in feces, which could comprise targets for pretreatment optimization and personalized nutritional therapy in pediatric CD.
AB - Background: Predicting response to exclusive enteral nutrition (EEN) in active Crohn's disease (CD) could lead to therapy personalization and pretreatment optimization. Objectives: 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. Methods: 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). Results: 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. Conclusions: We identify microbial signals and diet-related metabolites in feces, which could comprise targets for pretreatment optimization and personalized nutritional therapy in pediatric CD.
KW - Crohn's disease
KW - cytokines
KW - exclusive enteral nutrition
KW - metabolome
KW - microbiome
KW - o'link
KW - precision therapy
KW - short chain fatty acids
UR - http://www.scopus.com/inward/record.url?scp=85187567443&partnerID=8YFLogxK
U2 - 10.1016/j.ajcnut.2023.12.027
DO - 10.1016/j.ajcnut.2023.12.027
M3 - Article
C2 - 38569785
AN - SCOPUS:85187567443
SN - 0002-9165
VL - 119
SP - 885
EP - 895
JO - American Journal of Clinical Nutrition
JF - American Journal of Clinical Nutrition
IS - 4
ER -