Funded under the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.3, Theme 10.
Funded under the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.3, Theme 10.
Early nutrition with personalized mediterranean diet to decrease long-...
Coordinator
To develop and validate personally tailored algorithms for designing diets that optimise blood glucose levels in pregnant women and healthy children during the first 1000 days and long-term efficacy for weight maintenance in later ages (in connection with Spoke 4).
Provide an algorithm that predicts person-specific glycemic responses to various food to be used as a basis for providing individualized dietary recommendations (M24)
Validate the algorithms generated in the prospective trials on glucose and body weight maintenance (M36)
Recent studies have demonstrated that nutrition has an impact on long term health and on lifespan, highlighting that proper nutrition may reduce the prevalence of non-communicable chronic diseases and lead to healthier individuals with longer life expectancy. In this setting, early-life nutrition has a crucial role in affecting mid-term and long-term outcomes. Nutritional interventions even earlier during pregnancy may exert beneficial effects on the off springs. Despite the theoretical benefits of early interventions, the mechanisms underlying their effects are yet to be fully understood. In the last years Eran Elinav and colleagues developed and validated an algorithm enabling to predict the personalized postprandial glucose responses to food in adult healthy individuals (Zeevi et al., Cell. 2015; Rein et al., BMC Med. 2022). Hereby, we aim to develop personalized Mediterranean algorithm-based diets able to decrease postprandial blood glucose levels in pregnant women and children.
A prospective clinical trial will be conducted in 100 pregnant women and 100 healthy children. Participants will be randomized to receive either a standardized Mediterranean diet or a standardized western diet. Continuous glucose blood monitoring and serial collection of blood tests, stools samples for microbiome analysis and urine for metabolomics analysis will be gathered. Data on anthropometrics, blood pressure, dietary intake, physical activity, and sleep-wake rhythm will be prospectively collected with a specific app during the whole duration of the trial and integrated with the above-reported data to generate the algorithm. The specific algorithms provided from the trials on will be subsequently validated in two independent prospective cohorts.
In this study the rationale of developing an accurate algorithm for predicting the personalized post-prandial glucose response to food in children and pregnant women will be assessed. The development and further validation of the algorithms will allow defining personalized Mediterranean diet regimens that hopefully will decrease the incidence of hyperglycemia and gestational diabetes during pregnancy. In the same direction, the application of this model in pediatrics should have an immediate impact on the decrease of overweight and obesity. On the long-term, an overall reduction of the incidence of metabolic syndrome and diabetes is expected.
