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Nutritional strategies modulating the gut microbiome as a preventative and therapeutic approach in normal and pathological age-related cognitive decline: a systematic review of preclinical and clinical findings

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Nutr Neurosci. 2024 Jan 2:1-16. doi: 10.1080/1028415X.2023.2296727. Online ahead of print.

ABSTRACT

CONTEXT: The proportion of the elderly population is on the rise across the globe, and with it the prevalence of age-related neurodegenerative diseases. The gut microbiota, whose composition is highly regulated by dietary intake, has emerged as an exciting research field in neurology due to its pivotal role in modulating brain functions via the gut-brain axis.

OBJECTIVES: We aimed at conducting a systematic review of preclinical and clinical studies investigating the effects of dietary interventions on cognitive ageing in conjunction with changes in gut microbiota composition and functionality.

METHODS: PubMed and Scopus were searched using terms related to ageing, cognition, gut microbiota and dietary interventions. Studies were screened, selected based on previously determined inclusion and exclusion criteria, and evaluated for methodological quality using recommended risk of bias assessment tools.

RESULTS: A total of 32 studies (18 preclinical and 14 clinical) were selected for inclusion. We found that most of the animal studies showed significant positive intervention effects on cognitive behavior, while outcomes on cognition, microbiome features, and health parameters in humans were less pronounced. The effectiveness of dietary interventions depended markedly on the age, gender, degree of cognitive decline and baseline microbiome composition of participants.

CONCLUSION: To harness the full potential of microbiome-inspired nutrition for cognitive health, one of the main challenges remains to better understand the interplay between host, his microbiome, dietary exposures, whilst also taking into account environmental influences. Future research should aim toward making use of host-specific microbiome data to guide the development of personalized therapies.

PMID:38165747 | DOI:10.1080/1028415X.2023.2296727

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