Network-Based Multiomic Nutrient-Associated Predictive Models for Inflammatory Bowel Disease.

ABSTRACT:

Background

Inflammatory bowel disease (IBD) is a multifactorial disease involving a complex interplay between host physiology, the gut microbiome, and environmental factors such as diet and nutrition. Multiomic analyses may help to identify potential nutrient-associated omic predictors of IBD, allowing for the design of targeted dietary approaches for disease prevention and management.

Objectives

Our objective was to apply the bioinformatics tool, Consolidated Analysis of Network Topology and Regression Elements (CANTARE), to an integrated multiomics dataset to generate nutrient-associated predictive models for IBD.

Methods

We previously used a published data set of microbiome relative abundance (mb), untargeted metabolomics (met), and microbial-derived enzymes (e) in

SUBMITTER: Saint-Cyr M 

PROVIDER: S-EPMC12685511 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature