Investigating glucose response to Mediterranean and regular diets in healthy children in order to develop specific pediatric machine-learning for predicting the personalized glucose response to food for individual children.

The prediction will be based on multiple measurements, including blood tests, personal lifestyle and gut microbiome. This will allow investigators to design personalized Mediterranean machine-learning-based diets which may potentially reduce the burden of disease in adulthood as well as the burden of obesity in the pediatric age.

Early-life nutrition plays a critical role in mid-term and long-term metabolic and nutritional outcomes. However, the mechanisms underlying the effects of early nutrition on health are yet to be fully understood. Recently, it has been shown that alterations in intestinal microbiota and modulation of the immune response induced by food serve as the main mechanisms involved in the development of inflammatory conditions such as asthma, inflammatory bowel diseases, and cardiovascular disease. The Mediterranean diet has been shown to reduce the risk of cardiovascular disease, cancer, depression, colorectal cancer, diabetes, obesity, asthma, cognitive decline and premature death in general. Some studies also reported a positive effect of Mediterranean diet on glycemic control. However, whether this diet is a benefit to all individuals is unknown. Likewise, whether gut microbiome and its responses to diet is involved in these effects, or whether different Mediterranean diets may be optimized at the individualized level remains unstudied.

Recently, the investigators developed an algorithm enabling to predict the personalized postprandial glucose responses to food in adult healthy individuals. However, personalized nutrition was never tested on children.

In this study, children will be followed up in different bio-geographical locations. The primary aim of the study is to develop specific pediatric algorithms for predicting the personalized glucose response to food for individual children. This prediction will be based on multiple measurements, including blood and urine tests, anthropometric measurements, personal lifestyle and gut microbiome. This may allow the investigators to design personalized Mediterranean algorithm-based diets which may potentially reduce the burden of non-communicable disease in adulthood as well as the burden of obesity in the pediatric age.

Inclusion Criteria:

• Healthy children

• 6-11 years of age

• Tanner 1

  • Exclusion criteria:

• Acute disease 2 months prior to enrollment

• Chronic illness in the past 5 years, including inflammatory, metabolic, neoplastic, congenital and infectious disease.

• Use of medications (e.g. Antibiotics/antifungal, PPI, analgesics) and any antibiotics 3 months prior to the first visit, PPI one month prior to the beginning of the study or use of medication during the study.

• Treatment with anti-diabetic medications;

• Neuro-psychiatric disorders

• Cancer and recent anticancer treatment

• Eating disorders (Anorexia nervosa. Bulimia nervosa. Binge eating disorder, Night eating syndrome).

• Inability of the participant and/or nuclear family to follow and utilize the smartphone application.

• Dietary restrictions or specific dietary regimen

Healthy children will be invited to volunteer for the study.