Stratified and precision nutrition refers to disease management or prevention of disease onset, based on dietary interventions tailored to a person's characteristics, biology, gut microbiome, and environmental exposures. Such treatment models may lead to more effective management of inflammatory bowel disease (IBD) and reduce risk of disease development. This societal position paper aimed to report advances made in stratified and precision nutritional therapy in IBD. Following a structured literature search, limited to human studies, we identified four relevant themes: (a) nutritional epidemiology for risk prediction of IBD development, (b) food-based dietary interventions in IBD, (c) exclusive enteral nutrition (EEN) for Crohn's disease (CD) management, and (d) pre- and probiotics for IBD management. There is scarce literature upon which we can make recommendations for precision or stratified dietary therapy for IBD, both for risk of disease development and disease management. Certain single-nucleotide polymorphisms related to polyunsaturated fatty acid (PUFA) metabolism may modify the effect dietary PUFA have in increasing the risk of IBD development. Non-colonic CD, mild-to-moderate CD, and high microbiota richness may predict success of EEN and may be used both for prediction of treatment continuation, but also for early cessation in nonresponders. There is currently insufficient evidence to make recommendations for precision or stratified dietary therapy for patients with established IBD. Despite the great interest in stratified and precision nutrition, we currently lack data to support conclusive recommendations. Replication of early findings by independent research groups and within structured clinical interventions is required.
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.
- MeSH
- acetáty MeSH
- butyráty MeSH
- Crohnova nemoc * terapie metabolismus MeSH
- dítě MeSH
- enterální výživa MeSH
- fenylacetáty MeSH
- indukce remise MeSH
- lidé MeSH
- metabolom MeSH
- mikrobiota * MeSH
- prospektivní studie MeSH
- Check Tag
- dítě MeSH
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
