A Novel Interaction between a 23-SNP Genetic Risk Score and Monounsaturated Fatty Acid Intake on HbA1c Levels in Southeast Asian Women.
Padmini SekarArif Sabta AjiUtami AriyasraSri R SariNabila TasrifFinny Fitry YaniJulie Anne LovegroveIkhwan R SudjiNur Indrawati LipoetoKarani Santhanakrishnan VimaleswaranPublished in: Nutrients (2024)
Metabolic diseases result from interactions between genetic and lifestyle factors. Understanding the combined influences of single-nucleotide polymorphisms (SNPs) and lifestyle is crucial. This study employs genetic risk scores (GRS) to assess SNPs, providing insight beyond single gene/SNP studies by revealing synergistic effects. Here, we aim to investigate the association of a 23-SNP GRS with metabolic disease-related traits (obesity and type 2 diabetes) to understand if these associations are altered by lifestyle/dietary factors. For this study, 106 Minangkabau women were included and underwent physical, anthropometric, biochemical, dietary and genetic evaluations. The interaction of GRS with lifestyle factors was analyzed using linear regression models, adjusting for potential confounders. No statistically significant associations were observed between GRS and metabolic traits; however, this study demonstrates a novel interaction observed between 13-SNP GRS and monounsaturated fatty acid (MUFA) intake, and that it had an effect on HbA1c levels ( p = 0.026). Minangkabau women with low MUFA intake (≤7.0 g/day) and >13 risk alleles had significantly higher HbA1c levels ( p = 0.010). This finding has implications for public health, suggesting the need for large-scale studies to confirm our results before implementing dietary interventions in the Indonesian population. Identifying genetic influences on dietary response can inform personalized nutrition strategies to reduce the risk of metabolic disease.
Keyphrases
- genome wide
- dna methylation
- physical activity
- type diabetes
- copy number
- metabolic syndrome
- public health
- fatty acid
- weight loss
- cardiovascular disease
- insulin resistance
- gene expression
- weight gain
- pregnant women
- mental health
- body mass index
- risk assessment
- skeletal muscle
- high density
- transcription factor
- case control
- drug delivery
- breast cancer risk
- body composition
- genome wide identification