Background: Metabolic syndrome is a group of heritable metabolic traits that are highly associated with type 2 diabetes (T2DM). Classical interventions to T2DM include individual self-management of environmental risk factors such as improving diet quality, increasing physical activity and reducing smoking and alcohol consumptions, which decreases the risk of developing metabolic syndrome. However, it is poorly understood how the phenotypes of diabetes-related metabolic traits change with respect to lifestyle modifications at the individual level. Methods: In this study, we applied a whole-genome genotype-by-environment (GxE) interaction approach to describe how intermediate traits reflecting metabolic risk are affected by genetic variations and how this genetic risk can interact with lifestyle, which can vary, conditional on individual genetic differences. In the analysis, we used 12 diabetes-related metabolic traits and eight lifestyle covariates from the UK Biobank comprising 288,837 white British participants genotyped for 1,133,273 genome-wide single nucleotide polymorphisms. Findings: We found 17 GxE interactions, of which four modulated BMI and the others distributed across other traits. Modulation of genetic effects by physical activity was seen for four traits (glucose, HbA1c, C-reactive protein, systolic blood pressure), and by alcohol and smoking for three (BMI, glucose, waist-hip ratio; and BMI, diastolic and systolic blood pressure, respectively). We also found a number of significant phenotypic modulations by the lifestyle covariates, which were not attributed to the genetic effects in the model. Overall, modulation in the metabolic risk in response to the level of lifestyle covariates was clearly observed, and its direction and magnitude were varied depending on individual differences. We also showed that the metabolic risk inferred by our model was notably higher in T2DM prospective cases than controls. Interpretation: Our findings highlight the importance of individual genetic differences in the prevention and management of diabetes and suggest that the one-size-fits-all approach may not benefit all.
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