Nutritional protective mechanisms against gut inflammation

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Date
2013-01-15
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Publisher
Elsevier
Abstract

Inflammatory bowel disease (IBD) is a debilitating and widespread immune-mediated illness characterized by excessive inflammatory and effector mucosal responses leading to tissue destruction at the gastrointestinal tract. Interactions among the immune system, the commensal microbiota and the host genotype are thought to underlie the pathogenesis of IBD. However, the precise etiology of IBD remains unknown. Diet-induced changes in the composition of the gut microbiome can modulate the induction of regulatory versus effector immune responses at the gut mucosa and improve health outcomes. Therefore, manipulation of gut microbiota composition and the local production of microbial-derived metabolites by using prebiotics, probiotics and dietary fibers is being explored as a promising avenue of prophylactic and therapeutic intervention against gut inflammation. Prebiotics and fiber carbohydrates are fermented by resident microflora into short chain fatty acids (SCFAs) in the colon. SCFAs then activate peroxisome proliferator-activated receptor (PPAR)γ, a nuclear transcription factor with widely demonstrated anti-inflammatory efficacy in experimental IBD. The activation of PPARγ by naturally ocurring compounds such as conjugated linoleic acid, pomegranate seed oil-derived punicic acid, eleostearic acid and abscisic acid has been explored as nutritional interventions that suppress colitis by directly modulating the host immune response. The aim of this review is to summarize the status of innovative nutritional interventions against gastrointestinal inflammation, their proposed mechanisms of action, preclinical and clinical efficacy as well as bioinformatics and computational modeling approaches that accelerate discovery in nutritional and mucosal immunology research.

Description
Keywords
Inflammatory bowel disease, Prebiotics, Fibers, Probiotics, Conjugated linoleic acid, Punicic acid, Abscisic acid, Animal models, Computational modeling
Citation