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Published on: January 7, 2018
Lifestyle may modify the glucose-raising effect of genetic loci. A study in the Greek population
E Marouli1, S Kanoni2, M Dimitriou3
1Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece; National and Kapodistrian University of Athens, Faculty of Biology, Athens, Greece.
Background And Aims:
Lifestyle habits including dietary intake and physical activity are closely associated with multiple body processes including glucose metabolism and are known to affect human health. Recent genome-wide association studies have identified several single nucleotide polymorphisms (SNPs) associated with glucose levels. The hypothesis tested here is whether a healthy lifestyle assessed via a score is associated with glycaemic traits and whether there is an interaction between the lifestyle and known glucose-raising genetic variants in association with glycaemic traits.
Methods And Results:
Participants of Greek descent from the THISEAS study were included in this analysis. We developed a glucose preventive score (GPS) including dietary and physical activity characteristics. We also modelled a weighted genetic risk score (wGRS), based on 20 known glucose-raising loci, in order to investigate the impact of lifestyle-gene interaction on glucose levels. The GPS was observed to be significantly associated with lower glucose concentrations (β ± SE: -0.083 ± 0.021 mmol/L, P = 1.6 × 10(-04)) and the wGRS, as expected, with increased glucose levels (β ± SE: 0.020 ± 0.007 mmol/L, P = 8.4 × 10(-3)). The association of the wGRS with glucose levels was attenuated after interaction with the GPS. A higher GPS indicated decreasing glucose levels in the presence of an increasing wGRS (β interaction ± SE: -0.019 ± 0.007 mmol/L, P = 0.014).
Conclusion:
Our results indicate that lower glucose levels underlie a healthier lifestyle and also support an interaction between the wGRS for known glycaemic loci and GPS associated with lower glucose levels. These scores could be useful tools for monitoring glucose metabolism.
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