TY - JOUR T1 - Interactions of dietary whole-grain intake with fasting glucose- and insulin-related genetic loci in individuals of European descent: a meta-analysis of 14 cohort studies. JF - Diabetes Care Y1 - 2010 A1 - Nettleton, Jennifer A A1 - McKeown, Nicola M A1 - Kanoni, Stavroula A1 - Lemaitre, Rozenn N A1 - Hivert, Marie-France A1 - Ngwa, Julius A1 - van Rooij, Frank J A A1 - Sonestedt, Emily A1 - Wojczynski, Mary K A1 - Ye, Zheng A1 - Tanaka, Tosh A1 - Garcia, Melissa A1 - Anderson, Jennifer S A1 - Follis, Jack L A1 - Djoussé, Luc A1 - Mukamal, Kenneth A1 - Papoutsakis, Constantina A1 - Mozaffarian, Dariush A1 - Zillikens, M Carola A1 - Bandinelli, Stefania A1 - Bennett, Amanda J A1 - Borecki, Ingrid B A1 - Feitosa, Mary F A1 - Ferrucci, Luigi A1 - Forouhi, Nita G A1 - Groves, Christopher J A1 - Hallmans, Göran A1 - Harris, Tamara A1 - Hofman, Albert A1 - Houston, Denise K A1 - Hu, Frank B A1 - Johansson, Ingegerd A1 - Kritchevsky, Stephen B A1 - Langenberg, Claudia A1 - Launer, Lenore A1 - Liu, Yongmei A1 - Loos, Ruth J A1 - Nalls, Michael A1 - Orho-Melander, Marju A1 - Renstrom, Frida A1 - Rice, Kenneth A1 - Riserus, Ulf A1 - Rolandsson, Olov A1 - Rotter, Jerome I A1 - Saylor, Georgia A1 - Sijbrands, Eric J G A1 - Sjogren, Per A1 - Smith, Albert A1 - Steingrímsdóttir, Laufey A1 - Uitterlinden, André G A1 - Wareham, Nicholas J A1 - Prokopenko, Inga A1 - Pankow, James S A1 - van Duijn, Cornelia M A1 - Florez, Jose C A1 - Witteman, Jacqueline C M A1 - Dupuis, Josée A1 - Dedoussis, George V A1 - Ordovas, Jose M A1 - Ingelsson, Erik A1 - Cupples, L Adrienne A1 - Siscovick, David S A1 - Franks, Paul W A1 - Meigs, James B KW - Adult KW - Aged KW - Blood Glucose KW - Edible Grain KW - European Continental Ancestry Group KW - Fasting KW - Female KW - Genetic Loci KW - Genome-Wide Association Study KW - Genotype KW - Humans KW - Insulin KW - Male KW - Middle Aged KW - Polymorphism, Single Nucleotide AB -

OBJECTIVE: Whole-grain foods are touted for multiple health benefits, including enhancing insulin sensitivity and reducing type 2 diabetes risk. Recent genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) associated with fasting glucose and insulin concentrations in individuals free of diabetes. We tested the hypothesis that whole-grain food intake and genetic variation interact to influence concentrations of fasting glucose and insulin.

RESEARCH DESIGN AND METHODS: Via meta-analysis of data from 14 cohorts comprising ∼ 48,000 participants of European descent, we studied interactions of whole-grain intake with loci previously associated in GWAS with fasting glucose (16 loci) and/or insulin (2 loci) concentrations. For tests of interaction, we considered a P value <0.0028 (0.05 of 18 tests) as statistically significant.

RESULTS: Greater whole-grain food intake was associated with lower fasting glucose and insulin concentrations independent of demographics, other dietary and lifestyle factors, and BMI (β [95% CI] per 1-serving-greater whole-grain intake: -0.009 mmol/l glucose [-0.013 to -0.005], P < 0.0001 and -0.011 pmol/l [ln] insulin [-0.015 to -0.007], P = 0.0003). No interactions met our multiple testing-adjusted statistical significance threshold. The strongest SNP interaction with whole-grain intake was rs780094 (GCKR) for fasting insulin (P = 0.006), where greater whole-grain intake was associated with a smaller reduction in fasting insulin concentrations in those with the insulin-raising allele.

CONCLUSIONS: Our results support the favorable association of whole-grain intake with fasting glucose and insulin and suggest a potential interaction between variation in GCKR and whole-grain intake in influencing fasting insulin concentrations.

VL - 33 IS - 12 U1 - http://www.ncbi.nlm.nih.gov/pubmed/20693352?dopt=Abstract ER - TY - JOUR T1 - Consumption of meat is associated with higher fasting glucose and insulin concentrations regardless of glucose and insulin genetic risk scores: a meta-analysis of 50,345 Caucasians. JF - Am J Clin Nutr Y1 - 2015 A1 - Fretts, Amanda M A1 - Follis, Jack L A1 - Nettleton, Jennifer A A1 - Lemaitre, Rozenn N A1 - Ngwa, Julius S A1 - Wojczynski, Mary K A1 - Kalafati, Ioanna Panagiota A1 - Varga, Tibor V A1 - Frazier-Wood, Alexis C A1 - Houston, Denise K A1 - Lahti, Jari A1 - Ericson, Ulrika A1 - van den Hooven, Edith H A1 - Mikkilä, Vera A1 - Kiefte-de Jong, Jessica C A1 - Mozaffarian, Dariush A1 - Rice, Kenneth A1 - Renstrom, Frida A1 - North, Kari E A1 - McKeown, Nicola M A1 - Feitosa, Mary F A1 - Kanoni, Stavroula A1 - Smith, Caren E A1 - Garcia, Melissa E A1 - Tiainen, Anna-Maija A1 - Sonestedt, Emily A1 - Manichaikul, Ani A1 - van Rooij, Frank J A A1 - Dimitriou, Maria A1 - Raitakari, Olli A1 - Pankow, James S A1 - Djoussé, Luc A1 - Province, Michael A A1 - Hu, Frank B A1 - Lai, Chao-Qiang A1 - Keller, Margaux F A1 - Perälä, Mia-Maria A1 - Rotter, Jerome I A1 - Hofman, Albert A1 - Graff, Misa A1 - Kähönen, Mika A1 - Mukamal, Kenneth A1 - Johansson, Ingegerd A1 - Ordovas, Jose M A1 - Liu, Yongmei A1 - Männistö, Satu A1 - Uitterlinden, André G A1 - Deloukas, Panos A1 - Seppälä, Ilkka A1 - Psaty, Bruce M A1 - Cupples, L Adrienne A1 - Borecki, Ingrid B A1 - Franks, Paul W A1 - Arnett, Donna K A1 - Nalls, Mike A A1 - Eriksson, Johan G A1 - Orho-Melander, Marju A1 - Franco, Oscar H A1 - Lehtimäki, Terho A1 - Dedoussis, George V A1 - Meigs, James B A1 - Siscovick, David S KW - Blood Glucose KW - Cohort Studies KW - Genetic Association Studies KW - Genetic Predisposition to Disease KW - Genome-Wide Association Study KW - Humans KW - Hyperglycemia KW - Hyperinsulinism KW - Insulin KW - Insulin Resistance KW - Insulin-Secreting Cells KW - Meat KW - Meat Products KW - Middle Aged KW - Polymorphism, Single Nucleotide KW - Risk Factors AB -

BACKGROUND: Recent studies suggest that meat intake is associated with diabetes-related phenotypes. However, whether the associations of meat intake and glucose and insulin homeostasis are modified by genes related to glucose and insulin is unknown.

OBJECTIVE: We investigated the associations of meat intake and the interaction of meat with genotype on fasting glucose and insulin concentrations in Caucasians free of diabetes mellitus.

DESIGN: Fourteen studies that are part of the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium participated in the analysis. Data were provided for up to 50,345 participants. Using linear regression within studies and a fixed-effects meta-analysis across studies, we examined 1) the associations of processed meat and unprocessed red meat intake with fasting glucose and insulin concentrations; and 2) the interactions of processed meat and unprocessed red meat with genetic risk score related to fasting glucose or insulin resistance on fasting glucose and insulin concentrations.

RESULTS: Processed meat was associated with higher fasting glucose, and unprocessed red meat was associated with both higher fasting glucose and fasting insulin concentrations after adjustment for potential confounders [not including body mass index (BMI)]. For every additional 50-g serving of processed meat per day, fasting glucose was 0.021 mmol/L (95% CI: 0.011, 0.030 mmol/L) higher. Every additional 100-g serving of unprocessed red meat per day was associated with a 0.037-mmol/L (95% CI: 0.023, 0.051-mmol/L) higher fasting glucose concentration and a 0.049-ln-pmol/L (95% CI: 0.035, 0.063-ln-pmol/L) higher fasting insulin concentration. After additional adjustment for BMI, observed associations were attenuated and no longer statistically significant. The association of processed meat and fasting insulin did not reach statistical significance after correction for multiple comparisons. Observed associations were not modified by genetic loci known to influence fasting glucose or insulin resistance.

CONCLUSION: The association of higher fasting glucose and insulin concentrations with meat consumption was not modified by an index of glucose- and insulin-related single-nucleotide polymorphisms. Six of the participating studies are registered at clinicaltrials.gov as NCT0000513 (Atherosclerosis Risk in Communities), NCT00149435 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetics of Lipid Lowering Drugs and Diet Network), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).

VL - 102 IS - 5 U1 - http://www.ncbi.nlm.nih.gov/pubmed/26354543?dopt=Abstract ER - TY - JOUR T1 - Dietary fatty acids modulate associations between genetic variants and circulating fatty acids in plasma and erythrocyte membranes: Meta-analysis of nine studies in the CHARGE consortium. JF - Mol Nutr Food Res Y1 - 2015 A1 - Smith, Caren E A1 - Follis, Jack L A1 - Nettleton, Jennifer A A1 - Foy, Millennia A1 - Wu, Jason H Y A1 - Ma, Yiyi A1 - Tanaka, Toshiko A1 - Manichakul, Ani W A1 - Wu, Hongyu A1 - Chu, Audrey Y A1 - Steffen, Lyn M A1 - Fornage, Myriam A1 - Mozaffarian, Dariush A1 - Kabagambe, Edmond K A1 - Ferruci, Luigi A1 - Chen, Yii-Der Ida A1 - Rich, Stephen S A1 - Djoussé, Luc A1 - Ridker, Paul M A1 - Tang, Weihong A1 - McKnight, Barbara A1 - Tsai, Michael Y A1 - Bandinelli, Stefania A1 - Rotter, Jerome I A1 - Hu, Frank B A1 - Chasman, Daniel I A1 - Psaty, Bruce M A1 - Arnett, Donna K A1 - King, Irena B A1 - Sun, Qi A1 - Wang, Lu A1 - Lumley, Thomas A1 - Chiuve, Stephanie E A1 - Siscovick, David S A1 - Ordovas, Jose M A1 - Lemaitre, Rozenn N KW - Acetyltransferases KW - Acyltransferases KW - Adaptor Proteins, Signal Transducing KW - Carboxy-Lyases KW - Diet KW - Docosahexaenoic Acids KW - Eicosapentaenoic Acid KW - Erythrocyte Membrane KW - Fatty Acid Desaturases KW - Fatty Acids KW - Fatty Acids, Omega-3 KW - Female KW - Humans KW - Male KW - Middle Aged KW - Polymorphism, Single Nucleotide AB -

SCOPE: Tissue concentrations of omega-3 fatty acids may reduce cardiovascular disease risk, and genetic variants are associated with circulating fatty acids concentrations. Whether dietary fatty acids interact with genetic variants to modify circulating omega-3 fatty acids is unclear. We evaluated interactions between genetic variants and fatty acid intakes for circulating alpha-linoleic acid, eicosapentaenoic acid, docosahexaenoic acid, and docosapentaenoic acid.

METHODS AND RESULTS: We conducted meta-analyses (N = 11 668) evaluating interactions between dietary fatty acids and genetic variants (rs174538 and rs174548 in FADS1 (fatty acid desaturase 1), rs7435 in AGPAT3 (1-acyl-sn-glycerol-3-phosphate), rs4985167 in PDXDC1 (pyridoxal-dependent decarboxylase domain-containing 1), rs780094 in GCKR (glucokinase regulatory protein), and rs3734398 in ELOVL2 (fatty acid elongase 2)). Stratification by measurement compartment (plasma versus erthyrocyte) revealed compartment-specific interactions between FADS1 rs174538 and rs174548 and dietary alpha-linolenic acid and linoleic acid for docosahexaenoic acid and docosapentaenoic acid.

CONCLUSION: Our findings reinforce earlier reports that genetically based differences in circulating fatty acids may be partially due to differences in the conversion of fatty acid precursors. Further, fatty acids measurement compartment may modify gene-diet relationships, and considering compartment may improve the detection of gene-fatty acids interactions for circulating fatty acid outcomes.

VL - 59 IS - 7 U1 - http://www.ncbi.nlm.nih.gov/pubmed/25626431?dopt=Abstract ER - TY - JOUR T1 - Gene × dietary pattern interactions in obesity: analysis of up to 68 317 adults of European ancestry. JF - Hum Mol Genet Y1 - 2015 A1 - Nettleton, Jennifer A A1 - Follis, Jack L A1 - Ngwa, Julius S A1 - Smith, Caren E A1 - Ahmad, Shafqat A1 - Tanaka, Toshiko A1 - Wojczynski, Mary K A1 - Voortman, Trudy A1 - Lemaitre, Rozenn N A1 - Kristiansson, Kati A1 - Nuotio, Marja-Liisa A1 - Houston, Denise K A1 - Perälä, Mia-Maria A1 - Qi, Qibin A1 - Sonestedt, Emily A1 - Manichaikul, Ani A1 - Kanoni, Stavroula A1 - Ganna, Andrea A1 - Mikkilä, Vera A1 - North, Kari E A1 - Siscovick, David S A1 - Harald, Kennet A1 - McKeown, Nicola M A1 - Johansson, Ingegerd A1 - Rissanen, Harri A1 - Liu, Yongmei A1 - Lahti, Jari A1 - Hu, Frank B A1 - Bandinelli, Stefania A1 - Rukh, Gull A1 - Rich, Stephen A1 - Booij, Lisanne A1 - Dmitriou, Maria A1 - Ax, Erika A1 - Raitakari, Olli A1 - Mukamal, Kenneth A1 - Männistö, Satu A1 - Hallmans, Göran A1 - Jula, Antti A1 - Ericson, Ulrika A1 - Jacobs, David R A1 - van Rooij, Frank J A A1 - Deloukas, Panos A1 - Sjogren, Per A1 - Kähönen, Mika A1 - Djoussé, Luc A1 - Perola, Markus A1 - Barroso, Inês A1 - Hofman, Albert A1 - Stirrups, Kathleen A1 - Viikari, Jorma A1 - Uitterlinden, André G A1 - Kalafati, Ioanna P A1 - Franco, Oscar H A1 - Mozaffarian, Dariush A1 - Salomaa, Veikko A1 - Borecki, Ingrid B A1 - Knekt, Paul A1 - Kritchevsky, Stephen B A1 - Eriksson, Johan G A1 - Dedoussis, George V A1 - Qi, Lu A1 - Ferrucci, Luigi A1 - Orho-Melander, Marju A1 - Zillikens, M Carola A1 - Ingelsson, Erik A1 - Lehtimäki, Terho A1 - Renstrom, Frida A1 - Cupples, L Adrienne A1 - Loos, Ruth J F A1 - Franks, Paul W KW - Adult KW - Body Mass Index KW - Case-Control Studies KW - Diet, Western KW - Epistasis, Genetic KW - European Continental Ancestry Group KW - Female KW - Genetic Loci KW - Genome-Wide Association Study KW - Humans KW - Male KW - Obesity KW - Polymorphism, Single Nucleotide AB -

Obesity is highly heritable. Genetic variants showing robust associations with obesity traits have been identified through genome-wide association studies. We investigated whether a composite score representing healthy diet modifies associations of these variants with obesity traits. Totally, 32 body mass index (BMI)- and 14 waist-hip ratio (WHR)-associated single nucleotide polymorphisms were genotyped, and genetic risk scores (GRS) were calculated in 18 cohorts of European ancestry (n = 68 317). Diet score was calculated based on self-reported intakes of whole grains, fish, fruits, vegetables, nuts/seeds (favorable) and red/processed meats, sweets, sugar-sweetened beverages and fried potatoes (unfavorable). Multivariable adjusted, linear regression within each cohort followed by inverse variance-weighted, fixed-effects meta-analysis was used to characterize: (a) associations of each GRS with BMI and BMI-adjusted WHR and (b) diet score modification of genetic associations with BMI and BMI-adjusted WHR. Nominally significant interactions (P = 0.006-0.04) were observed between the diet score and WHR-GRS (but not BMI-GRS), two WHR loci (GRB14 rs10195252; LYPLAL1 rs4846567) and two BMI loci (LRRN6C rs10968576; MTIF3 rs4771122), for the respective BMI-adjusted WHR or BMI outcomes. Although the magnitudes of these select interactions were small, our data indicated that associations between genetic predisposition and obesity traits were stronger with a healthier diet. Our findings generate interesting hypotheses; however, experimental and functional studies are needed to determine their clinical relevance.

VL - 24 IS - 16 U1 - http://www.ncbi.nlm.nih.gov/pubmed/25994509?dopt=Abstract ER - TY - JOUR T1 - Gene-Environment Interactions of Circadian-Related Genes for Cardiometabolic Traits. JF - Diabetes Care Y1 - 2015 A1 - Dashti, Hassan S A1 - Follis, Jack L A1 - Smith, Caren E A1 - Tanaka, Toshiko A1 - Garaulet, Marta A1 - Gottlieb, Daniel J A1 - Hruby, Adela A1 - Jacques, Paul F A1 - Kiefte-de Jong, Jessica C A1 - Lamon-Fava, Stefania A1 - Scheer, Frank A J L A1 - Bartz, Traci M A1 - Kovanen, Leena A1 - Wojczynski, Mary K A1 - Frazier-Wood, Alexis C A1 - Ahluwalia, Tarunveer S A1 - Perälä, Mia-Maria A1 - Jonsson, Anna A1 - Muka, Taulant A1 - Kalafati, Ioanna P A1 - Mikkilä, Vera A1 - Ordovas, Jose M KW - Adult KW - Alleles KW - Blood Glucose KW - Circadian Rhythm Signaling Peptides and Proteins KW - Cohort Studies KW - Diabetes Mellitus, Type 2 KW - Diet, Fat-Restricted KW - European Continental Ancestry Group KW - Fasting KW - Female KW - Gene-Environment Interaction KW - Humans KW - Insulin Resistance KW - Male KW - Middle Aged KW - Multicenter Studies as Topic KW - Observational Studies as Topic KW - Phenotype KW - Polymorphism, Single Nucleotide KW - Sleep KW - Waist Circumference AB -

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/m(2) 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.

VL - 38 IS - 8 U1 - http://www.ncbi.nlm.nih.gov/pubmed/26084345?dopt=Abstract ER - TY - JOUR T1 - Habitual sleep duration is associated with BMI and macronutrient intake and may be modified by CLOCK genetic variants. JF - Am J Clin Nutr Y1 - 2015 A1 - Dashti, Hassan S A1 - Follis, Jack L A1 - Smith, Caren E A1 - Tanaka, Toshiko A1 - Cade, Brian E A1 - Gottlieb, Daniel J A1 - Hruby, Adela A1 - Jacques, Paul F A1 - Lamon-Fava, Stefania A1 - Richardson, Kris A1 - Saxena, Richa A1 - Scheer, Frank A J L A1 - Kovanen, Leena A1 - Bartz, Traci M A1 - Perälä, Mia-Maria A1 - Jonsson, Anna A1 - Frazier-Wood, Alexis C A1 - Kalafati, Ioanna-Panagiota A1 - Mikkilä, Vera A1 - Partonen, Timo A1 - Lemaitre, Rozenn N A1 - Lahti, Jari A1 - Hernandez, Dena G A1 - Toft, Ulla A1 - Johnson, W Craig A1 - Kanoni, Stavroula A1 - Raitakari, Olli T A1 - Perola, Markus A1 - Psaty, Bruce M A1 - Ferrucci, Luigi A1 - Grarup, Niels A1 - Highland, Heather M A1 - Rallidis, Loukianos A1 - Kähönen, Mika A1 - Havulinna, Aki S A1 - Siscovick, David S A1 - Räikkönen, Katri A1 - Jørgensen, Torben A1 - Rotter, Jerome I A1 - Deloukas, Panos A1 - Viikari, Jorma S A A1 - Mozaffarian, Dariush A1 - Linneberg, Allan A1 - Seppälä, Ilkka A1 - Hansen, Torben A1 - Salomaa, Veikko A1 - Gharib, Sina A A1 - Eriksson, Johan G A1 - Bandinelli, Stefania A1 - Pedersen, Oluf A1 - Rich, Stephen S A1 - Dedoussis, George A1 - Lehtimäki, Terho A1 - Ordovas, Jose M KW - Adult KW - Body Mass Index KW - CLOCK Proteins KW - Cohort Studies KW - Cross-Sectional Studies KW - Diet KW - Dietary Proteins KW - Energy Intake KW - European Continental Ancestry Group KW - Fatty Acids, Unsaturated KW - Female KW - Gene-Environment Interaction KW - Genetic Predisposition to Disease KW - Humans KW - Male KW - Middle Aged KW - Obesity KW - Polymorphism, Single Nucleotide KW - Sleep KW - Young Adult AB -

BACKGROUND: Short sleep duration has been associated with greater risks of obesity, hypertension, diabetes, and cardiovascular disease. Also, common genetic variants in the human Circadian Locomotor Output Cycles Kaput (CLOCK) show associations with ghrelin and total energy intake.

OBJECTIVES: We examined associations between habitual sleep duration, body mass index (BMI), and macronutrient intake and assessed whether CLOCK variants modify these associations.

DESIGN: We conducted inverse-variance weighted, fixed-effect meta-analyses of results of adjusted associations of sleep duration and BMI and macronutrient intake as percentages of total energy as well as interactions with CLOCK variants from 9 cohort studies including up to 14,906 participants of European descent from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium.

RESULTS: We observed a significant association between sleep duration and lower BMI (β ± SE = 0.16 ± 0.04, P < 0.0001) in the overall sample; however, associations between sleep duration and relative macronutrient intake were evident in age- and sex-stratified analyses only. We observed a significant association between sleep duration and lower saturated fatty acid intake in younger (aged 20-64 y) adults (men: 0.11 ± 0.06%, P = 0.03; women: 0.10 ± 0.05%, P = 0.04) and with lower carbohydrate (-0.31 ± 0.12%, P < 0.01), higher total fat (0.18 ± 0.09%, P = 0.05), and higher PUFA (0.05 ± 0.02%, P = 0.02) intakes in older (aged 65-80 y) women. In addition, the following 2 nominally significant interactions were observed: between sleep duration and rs12649507 on PUFA intake and between sleep duration and rs6858749 on protein intake.

CONCLUSIONS: Our results indicate that longer habitual sleep duration is associated with lower BMI and age- and sex-specific favorable dietary behaviors. Differences in the relative intake of specific macronutrients associated with short sleep duration could, at least in part, explain previously reported associations between short sleep duration and chronic metabolic abnormalities. In addition, the influence of obesity-associated CLOCK variants on the association between sleep duration and macronutrient intake suggests that longer habitual sleep duration could ameliorate the genetic predisposition to obesity via a favorable dietary profile.

VL - 101 IS - 1 U1 - http://www.ncbi.nlm.nih.gov/pubmed/25527757?dopt=Abstract ER - TY - JOUR T1 - Interaction of methylation-related genetic variants with circulating fatty acids on plasma lipids: a meta-analysis of 7 studies and methylation analysis of 3 studies in the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium. JF - Am J Clin Nutr Y1 - 2016 A1 - Ma, Yiyi A1 - Follis, Jack L A1 - Smith, Caren E A1 - Tanaka, Toshiko A1 - Manichaikul, Ani W A1 - Chu, Audrey Y A1 - Samieri, Cecilia A1 - Zhou, Xia A1 - Guan, Weihua A1 - Wang, Lu A1 - Biggs, Mary L A1 - Chen, Yii-der I A1 - Hernandez, Dena G A1 - Borecki, Ingrid A1 - Chasman, Daniel I A1 - Rich, Stephen S A1 - Ferrucci, Luigi A1 - Irvin, Marguerite Ryan A1 - Aslibekyan, Stella A1 - Zhi, Degui A1 - Tiwari, Hemant K A1 - Claas, Steven A A1 - Sha, Jin A1 - Kabagambe, Edmond K A1 - Lai, Chao-Qiang A1 - Parnell, Laurence D A1 - Lee, Yu-Chi A1 - Amouyel, Philippe A1 - Lambert, Jean-Charles A1 - Psaty, Bruce M A1 - King, Irena B A1 - Mozaffarian, Dariush A1 - McKnight, Barbara A1 - Bandinelli, Stefania A1 - Tsai, Michael Y A1 - Ridker, Paul M A1 - Ding, Jingzhong A1 - Mstat, Kurt Lohmant A1 - Liu, Yongmei A1 - Sotoodehnia, Nona A1 - Barberger-Gateau, Pascale A1 - Steffen, Lyn M A1 - Siscovick, David S A1 - Absher, Devin A1 - Arnett, Donna K A1 - Ordovas, Jose M A1 - Lemaitre, Rozenn N KW - Apolipoproteins E KW - ATP Binding Cassette Transporter 1 KW - Cholesterol, HDL KW - Cohort Studies KW - Diet KW - DNA Methylation KW - Eicosapentaenoic Acid KW - Epigenesis, Genetic KW - Fatty Acids KW - Gene Expression Regulation KW - Humans KW - Lipids KW - Polymorphism, Single Nucleotide KW - Promoter Regions, Genetic KW - Triglycerides AB -

BACKGROUND: DNA methylation is influenced by diet and single nucleotide polymorphisms (SNPs), and methylation modulates gene expression.

OBJECTIVE: We aimed to explore whether the gene-by-diet interactions on blood lipids act through DNA methylation.

DESIGN: We selected 7 SNPs on the basis of predicted relations in fatty acids, methylation, and lipids. We conducted a meta-analysis and a methylation and mediation analysis with the use of data from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) consortium and the ENCODE (Encyclopedia of DNA Elements) consortium.

RESULTS: On the basis of the meta-analysis of 7 cohorts in the CHARGE consortium, higher plasma HDL cholesterol was associated with fewer C alleles at ATP-binding cassette subfamily A member 1 (ABCA1) rs2246293 (β = -0.6 mg/dL, P = 0.015) and higher circulating eicosapentaenoic acid (EPA) (β = 3.87 mg/dL, P = 5.62 × 10(21)). The difference in HDL cholesterol associated with higher circulating EPA was dependent on genotypes at rs2246293, and it was greater for each additional C allele (β = 1.69 mg/dL, P = 0.006). In the GOLDN (Genetics of Lipid Lowering Drugs and Diet Network) study, higher ABCA1 promoter cg14019050 methylation was associated with more C alleles at rs2246293 (β = 8.84%, P = 3.51 × 10(18)) and lower circulating EPA (β = -1.46%, P = 0.009), and the mean difference in methylation of cg14019050 that was associated with higher EPA was smaller with each additional C allele of rs2246293 (β = -2.83%, P = 0.007). Higher ABCA1 cg14019050 methylation was correlated with lower ABCA1 expression (r = -0.61, P = 0.009) in the ENCODE consortium and lower plasma HDL cholesterol in the GOLDN study (r = -0.12, P = 0.0002). An additional mediation analysis was meta-analyzed across the GOLDN study, Cardiovascular Health Study, and the Multi-Ethnic Study of Atherosclerosis. Compared with the model without the adjustment of cg14019050 methylation, the model with such adjustment provided smaller estimates of the mean plasma HDL cholesterol concentration in association with both the rs2246293 C allele and EPA and a smaller difference by rs2246293 genotypes in the EPA-associated HDL cholesterol. However, the differences between 2 nested models were NS (P > 0.05).

CONCLUSION: We obtained little evidence that the gene-by-fatty acid interactions on blood lipids act through DNA methylation.

VL - 103 IS - 2 U1 - http://www.ncbi.nlm.nih.gov/pubmed/26791180?dopt=Abstract ER - TY - JOUR T1 - Genome-Wide Interactions with Dairy Intake for Body Mass Index in Adults of European Descent. JF - Mol Nutr Food Res Y1 - 2017 A1 - Smith, Caren E A1 - Follis, Jack L A1 - Dashti, Hassan S A1 - Tanaka, Toshiko A1 - Graff, Mariaelisa A1 - Fretts, Amanda M A1 - Kilpeläinen, Tuomas O A1 - Wojczynski, Mary K A1 - Richardson, Kris A1 - Nalls, Mike A A1 - Schulz, Christina-Alexandra A1 - Liu, Yongmei A1 - Frazier-Wood, Alexis C A1 - van Eekelen, Esther A1 - Wang, Carol A1 - de Vries, Paul S A1 - Mikkilä, Vera A1 - Rohde, Rebecca A1 - Psaty, Bruce M A1 - Hansen, Torben A1 - Feitosa, Mary F A1 - Lai, Chao-Qiang A1 - Houston, Denise K A1 - Ferruci, Luigi A1 - Ericson, Ulrika A1 - Wang, Zhe A1 - de Mutsert, Renée A1 - Oddy, Wendy H A1 - de Jonge, Ester A L A1 - Seppälä, Ilkka A1 - Justice, Anne E A1 - Lemaitre, Rozenn N A1 - Sørensen, Thorkild I A A1 - Province, Michael A A1 - Parnell, Laurence D A1 - Garcia, Melissa E A1 - Bandinelli, Stefania A1 - Orho-Melander, Marju A1 - Rich, Stephen S A1 - Rosendaal, Frits R A1 - Pennell, Craig E A1 - Kiefte-de Jong, Jessica C A1 - Kähönen, Mika A1 - Young, Kristin L A1 - Pedersen, Oluf A1 - Aslibekyan, Stella A1 - Rotter, Jerome I A1 - Mook-Kanamori, Dennis O A1 - Zillikens, M Carola A1 - Raitakari, Olli T A1 - North, Kari E A1 - Overvad, Kim A1 - Arnett, Donna K A1 - Hofman, Albert A1 - Lehtimäki, Terho A1 - Tjønneland, Anne A1 - Uitterlinden, André G A1 - Rivadeneira, Fernando A1 - Franco, Oscar H A1 - German, J Bruce A1 - Siscovick, David S A1 - Cupples, L Adrienne A1 - Ordovas, Jose M AB -

SCOPE: Body weight responds variably to the intake of dairy foods. Genetic variation may contribute to inter-individual variability in associations between body weight and dairy consumption.

METHODS AND RESULTS: A genome-wide interaction study to discover genetic variants that account for variation in BMI in the context of low-fat, high-fat and total dairy intake in cross-sectional analysis was conducted. Data from nine discovery studies (up to 25 513 European descent individuals) were meta-analyzed. Twenty-six genetic variants reached the selected significance threshold (p-interaction <10-7) , and six independent variants (LINC01512-rs7751666, PALM2/AKAP2-rs914359, ACTA2-rs1388, PPP1R12A-rs7961195, LINC00333-rs9635058, AC098847.1-rs1791355) were evaluated meta-analytically for replication of interaction in up to 17 675 individuals. Variant rs9635058 (128 kb 3' of LINC00333) was replicated (p-interaction = 0.004). In the discovery cohorts, rs9635058 interacted with dairy (p-interaction = 7.36 × 10-8) such that each serving of low-fat dairy was associated with 0.225 kg m-2 lower BMI per each additional copy of the effect allele (A). A second genetic variant (ACTA2-rs1388) approached interaction replication significance for low-fat dairy exposure.

CONCLUSION: Body weight responses to dairy intake may be modified by genotype, in that greater dairy intake may protect a genetic subgroup from higher body weight.

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