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Introduction: Carbohydrate intake and physical activity are related to glucose homeostasis, both being influenced by individual genetic makeup. However, the interactions between these 2 factors, as affected by genetics, on glycaemia have been scarcely reported. Objective: We focused on analysing the interplay between carbohydrate intake and physical activity levels on blood glucose, taking into account a genetic risk score (GRS), based on SNPs related to glucose/energy metabolism. Methods: A total of 1,271 individuals from the Food4Me cohort, who completed the nutritional intervention, were evaluated at baseline. We collected dietary information by using an online-validated food frequency questionnaire, a questionnaire on physical activity, blood biochemistry by analysis of dried blood spots, and by analysis of selected SNPs. Fifteen out of 31 SNPs, with recognized participation in carbohydrate/energy metabolism, were included in the component analyses. The GRS included risk alleles involved in the control of glycaemia or energy-yielding processes. Results: Data concerning anthropometric, clinical, metabolic, dietary intake, physical activity, and genetics related to blood glucose levels showed expected trends in European individuals of comparable sex and age, being categorized by lifestyle, BMI, and energy/carbohydrate intakes, in this Food4Me population. Blood glucose was inversely associated with physical activity level (β = −0.041, p = 0.013) and positively correlated with the GRS values (β = 0.015, p = 0.047). Interestingly, an interaction affecting glycaemia, concerning physical activity level with carbohydrate intake, was found (β = −0.060, p = 0.033), which also significantly depended on the genetic background (GRS). Conclusions: The relationships of carbohydrate intake and physical activity are important in understanding glucose homeostasis, where a role for the genetic background should be ascribed.

Objective: To investigate in a secondary analysis of a randomised trial the effects of a low-/high-fat diet and reported change from baseline in energy% from protein (prot%), in relation to changes in body size and metabolic factors. Methods: Obese adults (n = 771) were randomised to a 600 kcal energy-deficient low-fat (20-25 fat%) or high-fat (40-45 fat%) diet over 10 weeks. Dietary intake data at baseline and during the intervention were available in 585 completers. We used linear regression to calculate the combined effects of randomised group and groups of prot% change (2) on outcomes. Results: The low-fat group with >2 prot% increase lost 1.1 kg more weight (p = 0.03) and reduced cholesterol by 0.25 mmol/l more (p = 0.003) than the high-fat group with >2 prot% decrease. These differences were 2.5-fold and 1.8-fold greater than the differences between the low-fat and high-fat groups while not considering prot% change. The high-fat group reduced plasma triglycerides more than the low-fat group, but not compared to those in the low-fat group with >2 units prot% increase (p fat-protein interaction = 0.01). Conclusions: Under energy restriction, participants on a low-fat diet who had increased the percentage energy intake from protein showed the greatest reduction in weight and cholesterol, and a triglyceride reduction equally large to that of participants on a high-fat diet.