Dietary restriction (DR), including caloric restriction (CR), intermittent fasting (IF), and restriction of specific food compositions, can delay aging, and the main mechanisms include regulation of nutrient-sensing pathways and gut microbiota. However, the effects of DR regimens on longevity remain controversial, as some studies have demonstrated that IF, rather than CR or diet composition, influences longevity, while other studies have shown that the restricted-carbohydrate or -protein diets, rather than CR, determine health and longevity. Many factors, including DR-related factors (carbohydrate or protein composition, degree and duration of DR), and individual differences (health status, sex, genotype, and age of starting DR), would be used to explain the controversial anti-aging effects of DR, thus highlighting the necessity of precise DR intervention for anti-aging. Personalized DR intervention in humans is challenging because of the lack of accurate aging molecular biomarkers and vast individual variability. Using machine learning to build a predictive model based on the data set of clinical features, gut microbiome and metabolome, may be a good method to achieve precise DR intervention. Therefore, this review analyzed the anti-aging effects of various DR regimens, summarized their mechanisms and influencing factors, and proposed a future research direction for achieving personalized DR regimens for slowing aging.
Keywords: Dietary restriction; aging; gut microbiota; machine learning; personalized nutrition.