A genotype-guided nutritional intervention to reduce cardiometabolic risk factors in young adults: study protocol for a randomized controlled trial
Rodrigues, K., Mendes, M. M., Franco-Gedda, L. P., da Silva, N. R., Oliveira, M., Silva, F., Campos Corgosinhoa, F., Coelho, K. S., Lajolo, F. M., Aldrighi, J. M., Prado, C. M., Qi, L., Vimaleswaran, K. S.
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. Abstract/SummaryBackground & Aims Cardiometabolic diseases (CMD), including cardiovascular disease, obesity and diabetes, are major public health challenges influenced by lifestyle factors (e.g., diet), vitamin D status, and genetic predisposition. Single nucleotide polymorphisms (SNPs) contribute to genetic risk scores for CMD-related traits (M-GRS) and recent research suggests that genotype-based nutritional interventions have the potential to reduce these risks. This study aims to evaluate the effectiveness of genotype-guided nutritional interventions versus standard dietary recommendations in young adults. Methods This 12-month study includes a 6-month intervention phase and a 6-month free-living phase. Data will be collected at baseline, 3, 6 and 12 months. We plan to recruit young adults (aged 23-29) previously genotyped from the Obesity, Lifestyle, and Diabetes in Brazil (BOLD) study and randomized by BMI, sex, and M-GRS based on 34 SNPs. The control group will follow a standard Brazilian diet with CMD-related recommendations and 1000 IU of vitamin D3 daily. The personalized intervention group will receive a genotype-guided dietary plan based on gene-diet interactions for SNPs in the M-GRS, along with personalized vitamin D3 supplementation (1000 or 4000 IU) based on their genetic risk for deficiency (D-GRS). Body composition, biochemical markers and metabolomics will be assessed, with the reduction in body fat percentage as the primary outcome. Discussion This study will contribute to precision nutrition by assessing genotype-guided dietary recommendations for CMD risk management, potentially demonstrating how genetic information can optimize dietary interventions and reduce CMD burdens, improving overall health outcomes.
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