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ARS Home » Northeast Area » Boston, Massachusetts » Jean Mayer Human Nutrition Research Center On Aging » Research » Publications at this Location » Publication #348493

Research Project: Genomics, Nutrition, and Health

Location: Jean Mayer Human Nutrition Research Center On Aging

Title: Gene-environment interactions of circadian-related genes for cardiometabolic traits

Author
item Dashti, Hassan - Jean Mayer Human Nutrition Research Center On Aging At Tufts University
item Follis, Jack - University Of St Thomas
item Smith, Caren - Jean Mayer Human Nutrition Research Center On Aging At Tufts University
item Tanaka, Toshiko - National Institute On Aging (NIA, NIH)
item Garaulet, Marta - Universidad De Murcia
item Gottlieb, Daniel - Brigham & Women'S Hospital
item Hruby, Adela - Harvard University
item Jacques, Paul - Jean Mayer Human Nutrition Research Center On Aging At Tufts University
item Kiefte-de Jong, Jessica - Erasmus Medical Center
item Lamon-fava, Stefania - Jean Mayer Human Nutrition Research Center On Aging At Tufts University
item Scheer, Frank - Brigham & Women'S Hospital
item Bartz, Traci - University Of Washington
item Kovanen, Leena - National Institute For Health And Welfare (HELSINKI)
item Wojczynski, Mary - Washington University
item Frazier-wood, Alexis - Baylor University
item Ahluwalia, Tarunveer - University Of Copenhagen
item Perala, Mia-maria - National Institute For Health And Welfare (HELSINKI)
item Jonsson, Anna - University Of Copenhagen
item Muka, Taulant - Erasmus Medical Center
item Kalafati, Ionna - Harokopio University Of Athens
item Mikkila, Vera - University Of Helsinki
item Ordovas, Jose - Jean Mayer Human Nutrition Research Center On Aging At Tufts University

Submitted to: Diabetes Care
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/11/2015
Publication Date: 6/17/2015
Citation: Dashti, H., Follis, J.L., Smith, C.E., Tanaka, T., Garaulet, M.A., Gottlieb, D.J., Hruby, A., Jacques, P.F., Kiefte-De Jong, J.C., Lamon-Fava, S., Scheer, F.A., Bartz, T.M., Kovanen, L., Wojczynski, M.K., Frazier-Wood, A.C., Ahluwalia, T.S., Perala, M., Jonsson, A., Muka, T., Kalafati, I.P., Mikkila, V., Ordovas, J.M. 2015. Gene-environment interactions of circadian-related genes for cardiometabolic traits. Diabetes Care. 1-11. https://doi.org/10.2337/dc14-2709.

Interpretive Summary: The human biological clock is integral to many body processes including the sleep/wake cycle and metabolism. Dysregulation of the clock through genetic mutations disrupts the pathways regulated by the system and has been shown to result in increased risk for metabolic abnormalities, including insulin resistance and type 2 diabetes. The purpose of this investigation was to examine whether lifestyle modifications through diet or sleep can offset this genetic risk. We conducted meta-analyses of results of gene-by-diet interactions between dietary intake or sleep duration and the 5 genetic variants of interest on metabolic outcomes 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 Nutrition Working Group. No significant interactions were observed after accounting for multiple comparisons. However marginal associations suggest that lower carbohydrate intake and normal sleep durations ranging between 7h and 9h can potentially offset genetic risk conferred by the investigated genetic variants; however, this requires mechanistic confirmation to help improve our understanding of the biological clock. In addition, we found that diets lower in total fat intake and higher in total carbohydrate intake, combined with normal sleep duration ranging between 7h and 9h, are associated with better cardiometabolic profiles, independent of genetic background.

Technical 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], homeostasis model assessment-insulin resistance, BMI, waist circumference and HDL-cholesterol) in order 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 CHARGE Consortium. Results: We observed significant associations between relative macronutrient intakes and glycemic traits, 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 0.003mmol/L higher FG with each additional 1% carbohydrate intake in the presence of the T allele; between sleep duration and CRY2-rs11605924 for HDL-C with a 0.010mmol/L higher HDL-C 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 0.60kg/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.