Bitter Taste Receptor TAS2R38 Genetic Variation (rs10246939), Dietary Nutrient Intake, and Bio-Clinical Parameters in Koreans.
BenishJeong-Hwa ChoiPublished in: Clinical nutrition research (2023)
Differential bitterness perception associated with genetic polymorphism in the bitter taste receptor gene taste 2 receptor member 38 ( TAS2R38 ) may influence an individual's food preferences, nutrition consumption, and eventually chronic nutrition-related disorders including cardiovascular disease. Therefore, the effect of genetic variations on nutritional intake and clinical markers needs to be elaborated for health and disease prevention. In this study, we conducted sex-stratified analysis to examine the association between genetic variant TAS2R38 rs10246939 A > G with daily nutritional intake, blood pressure, and lipid parameters in Korean adults (males = 1,311 and females = 2,191). We used the data from the Multi Rural Communities Cohort, Korean Genome and Epidemiology Study. Findings suggested that the genetic variant TAS2R38 rs10246939 was associated with dietary intake of micronutrients including calcium (adjusted p = 0.007), phosphorous (adjusted p = 0.016), potassium (adjusted p = 0.022), vitamin C (adjusted p = 0.009), and vitamin E (adjusted p = 0.005) in females. However, this genetic variant did not influence blood glucose, lipid profile parameters, and other blood pressure markers. These may suggest that this genetic variation is associated with nutritional intake, but its clinical effect was not found. More studies are needed to explore whether TAS2R38 genotype may be a potential predictive marker for the risk of metabolic diseases via modulation of dietary intake.
Keyphrases
- genome wide
- blood pressure
- blood glucose
- copy number
- cardiovascular disease
- physical activity
- healthcare
- public health
- dna methylation
- weight gain
- type diabetes
- heart rate
- mental health
- hypertensive patients
- south africa
- adipose tissue
- machine learning
- metabolic syndrome
- human health
- risk factors
- skeletal muscle
- deep learning
- big data
- risk assessment
- electronic health record
- transcription factor
- genome wide identification
- drug induced