Gene-Environment Interactions of Circadian-Related Genes for Cardiometabolic Traits

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Gene-Environment Interactions of Circadian-Related Genes for Cardiometabolic Traits

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Title: Gene-Environment Interactions of Circadian-Related Genes for Cardiometabolic Traits
Author: Dashti, Hassan S.; Follis, Jack L.; Smith, Caren E.; Tanaka, Toshiko; Garaulet, Marta; Gottlieb, Daniel J.; Hruby, Adela; Jacques, Paul F.; Kiefte-de Jong, Jessica C.; Lamon-Fava, Stefania; Scheer, Frank A.J.L.; Bartz, Traci M.; Kovanen, Leena; Wojczynski, Mary K.; Frazier-Wood, Alexis C.; Ahluwalia, Tarunveer S.; Perälä, Mia-Maria; Jonsson, Anna; Muka, Taulant; Kalafati, Ioanna P.; Mikkilä, Vera; Ordovás, José M.

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Citation: Dashti, H. S., J. L. Follis, C. E. Smith, T. Tanaka, M. Garaulet, D. J. Gottlieb, A. Hruby, et al. 2015. “Gene-Environment Interactions of Circadian-Related Genes for Cardiometabolic Traits.” Diabetes Care 38 (8): 1456-1466. doi:10.2337/dc14-2709.
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Abstract: OBJECTIVE Common circadian-related gene variants associate with increased risk for metabolic alterations including type 2 diabetes. However, little is known about whether diet and sleep could modify associations between circadian-related variants (CLOCK-rs1801260, CRY2-rs11605924, MTNR1B-rs1387153, MTNR1B-rs10830963, NR1D1-rs2314339) and cardiometabolic traits (fasting glucose [FG], HOMA-insulin resistance, BMI, waist circumference, and HDL-cholesterol) to facilitate personalized recommendations. RESEARCH DESIGN AND METHODS We conducted inverse-variance weighted, fixed-effect meta-analyses of results of adjusted associations and interactions between dietary intake/sleep duration and selected variants on cardiometabolic traits from 15 cohort studies including up to 28,190 participants of European descent from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. RESULTS We observed significant associations between relative macronutrient intakes and glycemic traits and short sleep duration (<7 h) and higher FG and replicated known MTNR1B associations with glycemic traits. No interactions were evident after accounting for multiple comparisons. However, we observed nominally significant interactions (all P < 0.01) between carbohydrate intake and MTNR1B-rs1387153 for FG with a 0.003 mmol/L higher FG with each additional 1% carbohydrate intake in the presence of the T allele, between sleep duration and CRY2-rs11605924 for HDL-cholesterol with a 0.010 mmol/L higher HDL-cholesterol with each additional hour of sleep in the presence of the A allele, and between long sleep duration (≥9 h) and MTNR1B-rs1387153 for BMI with a 0.60 kg/m2 higher BMI with long sleep duration in the presence of the T allele relative to normal sleep duration (≥7 to <9 h). CONCLUSIONS Our results suggest that lower carbohydrate intake and normal sleep duration may ameliorate cardiometabolic abnormalities conferred by common circadian-related genetic variants. Until further mechanistic examination of the nominally significant interactions is conducted, recommendations applicable to the general population regarding diet—specifically higher carbohydrate and lower fat composition—and normal sleep duration should continue to be emphasized among individuals with the investigated circadian-related gene variants.
Published Version: doi:10.2337/dc14-2709
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