Sweet Taste Receptors' Genetic Variability in Advanced Potential Targets of Obesity

Abstract

Background: Obesity, mainly visceral obesity, causes a low-grade of chronic inflammation (meta-inflammation), associated with comorbidities such as type 2 diabetes, cardiovascular diseases, and certain cancers. Precision Nutrition aims to understand the bidirectional crosstalk between the genome and diet to improve human health. Additionally, by leveraging individual data, Precision Nutrition seeks to predict how people will respond to specific foods or dietary patterns, with the ultimate goal of providing personalized nutritional recommendations tailored to their unique needs and lifestyle factors, including poor dietary habits (e.g., high intake of sugar or saturated fatty acids, alcohol consumption, etc.) and sedentary habits, exacerbate obesity in genetically predisposed individuals. Genetic, metabolic, and environmental factors can play a crucial role during obesity. Objective: To investigate the effects of genetic variability in sweet taste receptors and their downstream signaling pathways in the gut-brain axis on anthropometry, biochemistry, and lifestyle variables. Methods: A sample of 676 volunteers (mean age of 42.22 ± 12 years, ranging from 18 to 73 years) from the database of the GENYAL platform for nutritional trials at the IMDEA Food Institute were included in this study. We present a first-in-class genetic chip, Glucosensing, designed to interrogate 25 single-nucleotide polymorphisms (SNPs) located in genes encoding sweet taste receptors and components of downstream signaling pathways. These include elements of the gut-brain axis and its associated metabolic networks, enabling a comprehensive analysis of individual variability in sweet taste perception and metabolic responses. Results: Several significant associations were found after correction for multiple comparisons, representing potential targets for personalized interventions.

Keywords: Precision Nutrition; gene-diet interactions; nutrigenetics; obesity; sweet taste signaling.

Figure 1

Study design indicating the main variables considered -anthropometric measurements, dietary intake (macro- and micronutrients), lifestyle factors (alcohol consumption, smoking, physical activity), and biochemical biomarkers.

Figure 2

This Figure indicates the genes selected in the glucosensing chip including the metabolic processes where they are implicated.

Figure 3

Graphical summary main results of the genotypic associations with various biochemical, anthropometrical, nutrient, and lifestyle variables of the study population.