The gut-brain axis (GBA) is a biochemical link that connects the central nervous system (CNS) and enteric nervous system (ENS). Clinical and experimental evidence suggests gut microbiota as a key regulator of the GBA. Microbes living in the gut not only interact locally with intestinal cells and the ENS but have also been found to modulate the CNS through neuroendocrine and metabolic pathways. Studies have also explored the involvement of gut microbiota dysbiosis in depression, anxiety, autism, stroke, and pathophysiology of other neurodegenerative diseases. Recent reports suggest that microbe-derived metabolites can influence host metabolism by acting as epigenetic regulators. Butyrate, an intestinal bacterial metabolite, is a known histone deacetylase inhibitor that has shown to improve learning and memory in animal models. Due to high disease variability amongst the population, a multi-omics approach that utilizes artificial intelligence and machine learning to analyze and integrate omics data is necessary to better understand the role of the GBA in pathogenesis of neurological disorders, to generate predictive models, and to develop precise and personalized therapeutics. This review examines our current understanding of epigenetic regulation of the GBA and proposes a framework to integrate multi-omics data for prediction, prevention, and development of precision health approaches to treat brain disorders.
Keywords: Alzheimer’s disease; apprentissage machine; axe intestin–cerveau; epigenetics; gut–brain axis; machine learning; maladie d’Alzheimer; maladies neurodégénératives; neurodegenerative diseases; épigénétique.