@article {1222, title = {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.}, journal = {Diabetes Care}, volume = {33}, year = {2010}, month = {2010 Dec}, pages = {2684-91}, abstract = {

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.

}, keywords = {Adult, Aged, Blood Glucose, Edible Grain, European Continental Ancestry Group, Fasting, Female, Genetic Loci, Genome-Wide Association Study, Genotype, Humans, Insulin, Male, Middle Aged, Polymorphism, Single Nucleotide}, issn = {1935-5548}, doi = {10.2337/dc10-1150}, author = {Nettleton, Jennifer A and McKeown, Nicola M and Kanoni, Stavroula and Lemaitre, Rozenn N and Hivert, Marie-France and Ngwa, Julius and van Rooij, Frank J A and Sonestedt, Emily and Wojczynski, Mary K and Ye, Zheng and Tanaka, Tosh and Garcia, Melissa and Anderson, Jennifer S and Follis, Jack L and Djouss{\'e}, Luc and Mukamal, Kenneth and Papoutsakis, Constantina and Mozaffarian, Dariush and Zillikens, M Carola and Bandinelli, Stefania and Bennett, Amanda J and Borecki, Ingrid B and Feitosa, Mary F and Ferrucci, Luigi and Forouhi, Nita G and Groves, Christopher J and Hallmans, G{\"o}ran and Harris, Tamara and Hofman, Albert and Houston, Denise K and Hu, Frank B and Johansson, Ingegerd and Kritchevsky, Stephen B and Langenberg, Claudia and Launer, Lenore and Liu, Yongmei and Loos, Ruth J and Nalls, Michael and Orho-Melander, Marju and Renstrom, Frida and Rice, Kenneth and Riserus, Ulf and Rolandsson, Olov and Rotter, Jerome I and Saylor, Georgia and Sijbrands, Eric J G and Sjogren, Per and Smith, Albert and Steingr{\'\i}msd{\'o}ttir, Laufey and Uitterlinden, Andr{\'e} G and Wareham, Nicholas J and Prokopenko, Inga and Pankow, James S and van Duijn, Cornelia M and Florez, Jose C and Witteman, Jacqueline C M and Dupuis, Jos{\'e}e and Dedoussis, George V and Ordovas, Jose M and Ingelsson, Erik and Cupples, L Adrienne and Siscovick, David S and Franks, Paul W and Meigs, James B} } @article {1311, title = {Genetic loci associated with plasma phospholipid n-3 fatty acids: a meta-analysis of genome-wide association studies from the CHARGE Consortium.}, journal = {PLoS Genet}, volume = {7}, year = {2011}, month = {2011 Jul}, pages = {e1002193}, abstract = {

Long-chain n-3 polyunsaturated fatty acids (PUFAs) can derive from diet or from α-linolenic acid (ALA) by elongation and desaturation. We investigated the association of common genetic variation with plasma phospholipid levels of the four major n-3 PUFAs by performing genome-wide association studies in five population-based cohorts comprising 8,866 subjects of European ancestry. Minor alleles of SNPs in FADS1 and FADS2 (desaturases) were associated with higher levels of ALA (p = 3 x 10$^{-}$$^{6}$$^{4}$) and lower levels of eicosapentaenoic acid (EPA, p = 5 x 10$^{-}$$^{5}$$^{8}$) and docosapentaenoic acid (DPA, p = 4 x 10$^{-}${\textonesuperior}$^{5}$$^{4}$). Minor alleles of SNPs in ELOVL2 (elongase) were associated with higher EPA (p = 2 x 10$^{-}${\textonesuperior}{\texttwosuperior}) and DPA (p = 1 x 10$^{-}$$^{4}${\textthreesuperior}) and lower docosahexaenoic acid (DHA, p = 1 x 10$^{-}${\textonesuperior}$^{5}$). In addition to genes in the n-3 pathway, we identified a novel association of DPA with several SNPs in GCKR (glucokinase regulator, p = 1 x 10$^{-}$$^{8}$). We observed a weaker association between ALA and EPA among carriers of the minor allele of a representative SNP in FADS2 (rs1535), suggesting a lower rate of ALA-to-EPA conversion in these subjects. In samples of African, Chinese, and Hispanic ancestry, associations of n-3 PUFAs were similar with a representative SNP in FADS1 but less consistent with a representative SNP in ELOVL2. Our findings show that common variation in n-3 metabolic pathway genes and in GCKR influences plasma phospholipid levels of n-3 PUFAs in populations of European ancestry and, for FADS1, in other ancestries.

}, keywords = {Alleles, Continental Population Groups, Fatty Acids, Omega-3, Female, Genetic Loci, Genome-Wide Association Study, Humans, Male, Metabolic Networks and Pathways, Polymorphism, Single Nucleotide}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1002193}, author = {Lemaitre, Rozenn N and Tanaka, Toshiko and Tang, Weihong and Manichaikul, Ani and Foy, Millennia and Kabagambe, Edmond K and Nettleton, Jennifer A and King, Irena B and Weng, Lu-Chen and Bhattacharya, Sayanti and Bandinelli, Stefania and Bis, Joshua C and Rich, Stephen S and Jacobs, David R and Cherubini, Antonio and McKnight, Barbara and Liang, Shuang and Gu, Xiangjun and Rice, Kenneth and Laurie, Cathy C and Lumley, Thomas and Browning, Brian L and Psaty, Bruce M and Chen, Yii-der I and Friedlander, Yechiel and Djouss{\'e}, Luc and Wu, Jason H Y and Siscovick, David S and Uitterlinden, Andr{\'e} G and Arnett, Donna K and Ferrucci, Luigi and Fornage, Myriam and Tsai, Michael Y and Mozaffarian, Dariush and Steffen, Lyn M} } @article {1308, title = {Total zinc intake may modify the glucose-raising effect of a zinc transporter (SLC30A8) variant: a 14-cohort meta-analysis.}, journal = {Diabetes}, volume = {60}, year = {2011}, month = {2011 Sep}, pages = {2407-16}, abstract = {

OBJECTIVE: Many genetic variants have been associated with glucose homeostasis and type 2 diabetes in genome-wide association studies. Zinc is an essential micronutrient that is important for β-cell function and glucose homeostasis. We tested the hypothesis that zinc intake could influence the glucose-raising effect of specific variants.

RESEARCH DESIGN AND METHODS: We conducted a 14-cohort meta-analysis to assess the interaction of 20 genetic variants known to be related to glycemic traits and zinc metabolism with dietary zinc intake (food sources) and a 5-cohort meta-analysis to assess the interaction with total zinc intake (food sources and supplements) on fasting glucose levels among individuals of European ancestry without diabetes.

RESULTS: We observed a significant association of total zinc intake with lower fasting glucose levels (β-coefficient {\textpm} SE per 1 mg/day of zinc intake: -0.0012 {\textpm} 0.0003 mmol/L, summary P value = 0.0003), while the association of dietary zinc intake was not significant. We identified a nominally significant interaction between total zinc intake and the SLC30A8 rs11558471 variant on fasting glucose levels (β-coefficient {\textpm} SE per A allele for 1 mg/day of greater total zinc intake: -0.0017 {\textpm} 0.0006 mmol/L, summary interaction P value = 0.005); this result suggests a stronger inverse association between total zinc intake and fasting glucose in individuals carrying the glucose-raising A allele compared with individuals who do not carry it. None of the other interaction tests were statistically significant.

CONCLUSIONS: Our results suggest that higher total zinc intake may attenuate the glucose-raising effect of the rs11558471 SLC30A8 (zinc transporter) variant. Our findings also support evidence for the association of higher total zinc intake with lower fasting glucose levels.

}, keywords = {Blood Glucose, Cation Transport Proteins, Cohort Studies, Humans, Polymorphism, Single Nucleotide, Zinc, Zinc Transporter 8}, issn = {1939-327X}, doi = {10.2337/db11-0176}, author = {Kanoni, Stavroula and Nettleton, Jennifer A and Hivert, Marie-France and Ye, Zheng and van Rooij, Frank J A and Shungin, Dmitry and Sonestedt, Emily and Ngwa, Julius S and Wojczynski, Mary K and Lemaitre, Rozenn N and Gustafsson, Stefan and Anderson, Jennifer S and Tanaka, Toshiko and Hindy, George and Saylor, Georgia and Renstrom, Frida and Bennett, Amanda J and van Duijn, Cornelia M and Florez, Jose C and Fox, Caroline S and Hofman, Albert and Hoogeveen, Ron C and Houston, Denise K and Hu, Frank B and Jacques, Paul F and Johansson, Ingegerd and Lind, Lars and Liu, Yongmei and McKeown, Nicola and Ordovas, Jose and Pankow, James S and Sijbrands, Eric J G and Syv{\"a}nen, Ann-Christine and Uitterlinden, Andr{\'e} G and Yannakoulia, Mary and Zillikens, M Carola and Wareham, Nick J and Prokopenko, Inga and Bandinelli, Stefania and Forouhi, Nita G and Cupples, L Adrienne and Loos, Ruth J and Hallmans, G{\"o}ran and Dupuis, Jos{\'e}e and Langenberg, Claudia and Ferrucci, Luigi and Kritchevsky, Stephen B and McCarthy, Mark I and Ingelsson, Erik and Borecki, Ingrid B and Witteman, Jacqueline C M and Orho-Melander, Marju and Siscovick, David S and Meigs, James B and Franks, Paul W and Dedoussis, George V} } @article {5880, title = {Genome-wide association study identifies novel loci associated with concentrations of four plasma phospholipid fatty acids in the de novo lipogenesis pathway: results from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortiu}, journal = {Circ Cardiovasc Genet}, volume = {6}, year = {2013}, month = {2013 Apr}, pages = {171-83}, abstract = {

BACKGROUND- Palmitic acid (16:0), stearic acid (18:0), palmitoleic acid (16:1n-7), and oleic acid (18:1n-9) are major saturated and monounsaturated fatty acids that affect cellular signaling and metabolic pathways. They are synthesized via de novo lipogenesis and are the main saturated and monounsaturated fatty acids in the diet. Levels of these fatty acids have been linked to diseases including type 2 diabetes mellitus and coronary heart disease. METHODS AND RESULTS- Genome-wide association studies were conducted in 5 population-based cohorts comprising 8961 participants of European ancestry to investigate the association of common genetic variation with plasma levels of these 4 fatty acids. We identified polymorphisms in 7 novel loci associated with circulating levels of >=1 of these fatty acids. ALG14 (asparagine-linked glycosylation 14 homolog) polymorphisms were associated with higher 16:0 (P=2.7{\texttimes}10(-11)) and lower 18:0 (P=2.2{\texttimes}10(-18)). FADS1 and FADS2 (desaturases) polymorphisms were associated with higher 16:1n-7 (P=6.6{\texttimes}10(-13)) and 18:1n-9 (P=2.2{\texttimes}10(-32)) and lower 18:0 (P=1.3{\texttimes}10(-20)). LPGAT1 (lysophosphatidylglycerol acyltransferase) polymorphisms were associated with lower 18:0 (P=2.8{\texttimes}10(-9)). GCKR (glucokinase regulator; P=9.8{\texttimes}10(-10)) and HIF1AN (factor inhibiting hypoxia-inducible factor-1; P=5.7{\texttimes}10(-9)) polymorphisms were associated with higher 16:1n-7, whereas PKD2L1 (polycystic kidney disease 2-like 1; P=5.7{\texttimes}10(-15)) and a locus on chromosome 2 (not near known genes) were associated with lower 16:1n-7 (P=4.1{\texttimes}10(-8)). CONCLUSIONS- Our findings provide novel evidence that common variations in genes with diverse functions, including protein-glycosylation, polyunsaturated fatty acid metabolism, phospholipid modeling, and glucose- and oxygen-sensing pathways, are associated with circulating levels of 4 fatty acids in the de novo lipogenesis pathway. These results expand our knowledge of genetic factors relevant to de novo lipogenesis and fatty acid biology.

}, keywords = {Adult, Aged, Chromosomes, Human, Pair 2, Cohort Studies, Coronary Disease, Diabetes Mellitus, Type 2, Fatty Acids, Monounsaturated, Female, Genetic Loci, Genome-Wide Association Study, Genotype, Humans, Linkage Disequilibrium, Lipogenesis, Male, Middle Aged, Oleic Acid, Palmitic Acid, Polymorphism, Single Nucleotide, Stearic Acids}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.112.964619}, author = {Wu, Jason H Y and Lemaitre, Rozenn N and Manichaikul, Ani and Guan, Weihua and Tanaka, Toshiko and Foy, Millennia and Kabagambe, Edmond K and Djouss{\'e}, Luc and Siscovick, David and Fretts, Amanda M and Johnson, Catherine and King, Irena B and Psaty, Bruce M and McKnight, Barbara and Rich, Stephen S and Chen, Yii-der I and Nettleton, Jennifer A and Tang, Weihong and Bandinelli, Stefania and Jacobs, David R and Browning, Brian L and Laurie, Cathy C and Gu, Xiangjun and Tsai, Michael Y and Steffen, Lyn M and Ferrucci, Luigi and Fornage, Myriam and Mozaffarian, Dariush} } @article {6163, title = {Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake.}, journal = {Am J Clin Nutr}, volume = {97}, year = {2013}, month = {2013 Jun}, pages = {1395-402}, abstract = {

BACKGROUND: Macronutrient intake varies substantially between individuals, and there is evidence that this variation is partly accounted for by genetic variants.

OBJECTIVE: The objective of the study was to identify common genetic variants that are associated with macronutrient intake.

DESIGN: We performed 2-stage genome-wide association (GWA) meta-analysis of macronutrient intake in populations of European descent. Macronutrients were assessed by using food-frequency questionnaires and analyzed as percentages of total energy consumption from total fat, protein, and carbohydrate. From the discovery GWA (n = 38,360), 35 independent loci associated with macronutrient intake at P < 5 {\texttimes} 10(-6) were identified and taken forward to replication in 3 additional cohorts (n = 33,533) from the DietGen Consortium. For one locus, fat mass obesity-associated protein (FTO), cohorts with Illumina MetaboChip genotype data (n = 7724) provided additional replication data.

RESULTS: A variant in the chromosome 19 locus (rs838145) was associated with higher carbohydrate (β {\textpm} SE: 0.25 {\textpm} 0.04\%; P = 1.68 {\texttimes} 10(-8)) and lower fat (β {\textpm} SE: -0.21 {\textpm} 0.04\%; P = 1.57 {\texttimes} 10(-9)) consumption. A candidate gene in this region, fibroblast growth factor 21 (FGF21), encodes a fibroblast growth factor involved in glucose and lipid metabolism. The variants in this locus were associated with circulating FGF21 protein concentrations (P < 0.05) but not mRNA concentrations in blood or brain. The body mass index (BMI)-increasing allele of the FTO variant (rs1421085) was associated with higher protein intake (β {\textpm} SE: 0.10 {\textpm} 0.02\%; P = 9.96 {\texttimes} 10(-10)), independent of BMI (after adjustment for BMI, β {\textpm} SE: 0.08 {\textpm} 0.02\%; P = 3.15 {\texttimes} 10(-7)).

CONCLUSION: Our results indicate that variants in genes involved in nutrient metabolism and obesity are associated with macronutrient consumption in humans. Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetic and Environmental Determinants of Triglycerides), NCT01331512 (InCHIANTI Study), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).

}, keywords = {Alleles, Atherosclerosis, Body Mass Index, Dietary Carbohydrates, Dietary Fats, Dietary Proteins, Energy Intake, European Continental Ancestry Group, Fibroblast Growth Factors, Follow-Up Studies, Gene-Environment Interaction, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Life Style, Obesity, Polymorphism, Single Nucleotide, Prospective Studies, Quantitative Trait Loci, Surveys and Questionnaires}, issn = {1938-3207}, doi = {10.3945/ajcn.112.052183}, author = {Tanaka, Toshiko and Ngwa, Julius S and van Rooij, Frank J A and Zillikens, M Carola and Wojczynski, Mary K and Frazier-Wood, Alexis C and Houston, Denise K and Kanoni, Stavroula and Lemaitre, Rozenn N and Luan, Jian{\textquoteright}an and Mikkil{\"a}, Vera and Renstrom, Frida and Sonestedt, Emily and Zhao, Jing Hua and Chu, Audrey Y and Qi, Lu and Chasman, Daniel I and de Oliveira Otto, Marcia C and Dhurandhar, Emily J and Feitosa, Mary F and Johansson, Ingegerd and Khaw, Kay-Tee and Lohman, Kurt K and Manichaikul, Ani and McKeown, Nicola M and Mozaffarian, Dariush and Singleton, Andrew and Stirrups, Kathleen and Viikari, Jorma and Ye, Zheng and Bandinelli, Stefania and Barroso, In{\^e}s and Deloukas, Panos and Forouhi, Nita G and Hofman, Albert and Liu, Yongmei and Lyytik{\"a}inen, Leo-Pekka and North, Kari E and Dimitriou, Maria and Hallmans, G{\"o}ran and K{\"a}h{\"o}nen, Mika and Langenberg, Claudia and Ordovas, Jose M and Uitterlinden, Andr{\'e} G and Hu, Frank B and Kalafati, Ioanna-Panagiota and Raitakari, Olli and Franco, Oscar H and Johnson, Andrew and Emilsson, Valur and Schrack, Jennifer A and Semba, Richard D and Siscovick, David S and Arnett, Donna K and Borecki, Ingrid B and Franks, Paul W and Kritchevsky, Stephen B and Lehtim{\"a}ki, Terho and Loos, Ruth J F and Orho-Melander, Marju and Rotter, Jerome I and Wareham, Nicholas J and Witteman, Jacqueline C M and Ferrucci, Luigi and Dedoussis, George and Cupples, L Adrienne and Nettleton, Jennifer A} } @article {5879, title = {Higher magnesium intake is associated with lower fasting glucose and insulin, with no evidence of interaction with select genetic loci, in a meta-analysis of 15 CHARGE Consortium Studies.}, journal = {J Nutr}, volume = {143}, year = {2013}, month = {2013 Mar}, pages = {345-53}, abstract = {

Favorable associations between magnesium intake and glycemic traits, such as fasting glucose and insulin, are observed in observational and clinical studies, but whether genetic variation affects these associations is largely unknown. We hypothesized that single nucleotide polymorphisms (SNPs) associated with either glycemic traits or magnesium metabolism affect the association between magnesium intake and fasting glucose and insulin. Fifteen studies from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium provided data from up to 52,684 participants of European descent without known diabetes. In fixed-effects meta-analyses, we quantified 1) cross-sectional associations of dietary magnesium intake with fasting glucose (mmol/L) and insulin (ln-pmol/L) and 2) interactions between magnesium intake and SNPs related to fasting glucose (16 SNPs), insulin (2 SNPs), or magnesium (8 SNPs) on fasting glucose and insulin. After adjustment for age, sex, energy intake, BMI, and behavioral risk factors, magnesium (per 50-mg/d increment) was inversely associated with fasting glucose [β = -0.009 mmol/L (95\% CI: -0.013, -0.005), P < 0.0001] and insulin [-0.020 ln-pmol/L (95\% CI: -0.024, -0.017), P < 0.0001]. No magnesium-related SNP or interaction between any SNP and magnesium reached significance after correction for multiple testing. However, rs2274924 in magnesium transporter-encoding TRPM6 showed a nominal association (uncorrected P = 0.03) with glucose, and rs11558471 in SLC30A8 and rs3740393 near CNNM2 showed a nominal interaction (uncorrected, both P = 0.02) with magnesium on glucose. Consistent with other studies, a higher magnesium intake was associated with lower fasting glucose and insulin. Nominal evidence of TRPM6 influence and magnesium interaction with select loci suggests that further investigation is warranted.

}, keywords = {Blood Glucose, Female, Genetic Loci, Humans, Insulin, Magnesium, Male, Polymorphism, Single Nucleotide, Trace Elements, TRPM Cation Channels}, issn = {1541-6100}, doi = {10.3945/jn.112.172049}, author = {Hruby, Adela and Ngwa, Julius S and Renstrom, Frida and Wojczynski, Mary K and Ganna, Andrea and Hallmans, G{\"o}ran and Houston, Denise K and Jacques, Paul F and Kanoni, Stavroula and Lehtim{\"a}ki, Terho and Lemaitre, Rozenn N and Manichaikul, Ani and North, Kari E and Ntalla, Ioanna and Sonestedt, Emily and Tanaka, Toshiko and van Rooij, Frank J A and Bandinelli, Stefania and Djouss{\'e}, Luc and Grigoriou, Efi and Johansson, Ingegerd and Lohman, Kurt K and Pankow, James S and Raitakari, Olli T and Riserus, Ulf and Yannakoulia, Mary and Zillikens, M Carola and Hassanali, Neelam and Liu, Yongmei and Mozaffarian, Dariush and Papoutsakis, Constantina and Syv{\"a}nen, Ann-Christine and Uitterlinden, Andr{\'e} G and Viikari, Jorma and Groves, Christopher J and Hofman, Albert and Lind, Lars and McCarthy, Mark I and Mikkil{\"a}, Vera and Mukamal, Kenneth and Franco, Oscar H and Borecki, Ingrid B and Cupples, L Adrienne and Dedoussis, George V and Ferrucci, Luigi and Hu, Frank B and Ingelsson, Erik and K{\"a}h{\"o}nen, Mika and Kao, W H Linda and Kritchevsky, Stephen B and Orho-Melander, Marju and Prokopenko, Inga and Rotter, Jerome I and Siscovick, David S and Witteman, Jacqueline C M and Franks, Paul W and Meigs, James B and McKeown, Nicola M and Nettleton, Jennifer A} } @article {6938, title = {FTO genetic variants, dietary intake and body mass index: insights from 177,330 individuals.}, journal = {Hum Mol Genet}, volume = {23}, year = {2014}, month = {2014 Dec 20}, pages = {6961-72}, abstract = {

FTO is the strongest known genetic susceptibility locus for obesity. Experimental studies in animals suggest the potential roles of FTO in regulating food intake. The interactive relation among FTO variants, dietary intake and body mass index (BMI) is complex and results from previous often small-scale studies in humans are highly inconsistent. We performed large-scale analyses based on data from 177,330 adults (154 439 Whites, 5776 African Americans and 17 115 Asians) from 40 studies to examine: (i) the association between the FTO-rs9939609 variant (or a proxy single-nucleotide polymorphism) and total energy and macronutrient intake and (ii) the interaction between the FTO variant and dietary intake on BMI. The minor allele (A-allele) of the FTO-rs9939609 variant was associated with higher BMI in Whites (effect per allele = 0.34 [0.31, 0.37] kg/m(2), P = 1.9 {\texttimes} 10(-105)), and all participants (0.30 [0.30, 0.35] kg/m(2), P = 3.6 {\texttimes} 10(-107)). The BMI-increasing allele of the FTO variant showed a significant association with higher dietary protein intake (effect per allele = 0.08 [0.06, 0.10] \%, P = 2.4 {\texttimes} 10(-16)), and relative weak associations with lower total energy intake (-6.4 [-10.1, -2.6] kcal/day, P = 0.001) and lower dietary carbohydrate intake (-0.07 [-0.11, -0.02] \%, P = 0.004). The associations with protein (P = 7.5 {\texttimes} 10(-9)) and total energy (P = 0.002) were attenuated but remained significant after adjustment for BMI. We did not find significant interactions between the FTO variant and dietary intake of total energy, protein, carbohydrate or fat on BMI. Our findings suggest a positive association between the BMI-increasing allele of FTO variant and higher dietary protein intake and offer insight into potential link between FTO, dietary protein intake and adiposity.

}, keywords = {Adult, African Americans, Aged, Alleles, Asian Continental Ancestry Group, Body Mass Index, Dietary Carbohydrates, Dietary Fats, Dietary Proteins, Energy Intake, European Continental Ancestry Group, Female, Gene Frequency, Humans, Male, Middle Aged, Obesity, Polymorphism, Single Nucleotide, Proteins}, issn = {1460-2083}, doi = {10.1093/hmg/ddu411}, author = {Qi, Qibin and Kilpel{\"a}inen, Tuomas O and Downer, Mary K and Tanaka, Toshiko and Smith, Caren E and Sluijs, Ivonne and Sonestedt, Emily and Chu, Audrey Y and Renstrom, Frida and Lin, Xiaochen and {\"A}ngquist, Lars H and Huang, Jinyan and Liu, Zhonghua and Li, Yanping and Asif Ali, Muhammad and Xu, Min and Ahluwalia, Tarunveer Singh and Boer, Jolanda M A and Chen, Peng and Daimon, Makoto and Eriksson, Johan and Perola, Markus and Friedlander, Yechiel and Gao, Yu-Tang and Heppe, Denise H M and Holloway, John W and Houston, Denise K and Kanoni, Stavroula and Kim, Yu-Mi and Laaksonen, Maarit A and J{\"a}{\"a}skel{\"a}inen, Tiina and Lee, Nanette R and Lehtim{\"a}ki, Terho and Lemaitre, Rozenn N and Lu, Wei and Luben, Robert N and Manichaikul, Ani and M{\"a}nnist{\"o}, Satu and Marques-Vidal, Pedro and Monda, Keri L and Ngwa, Julius S and Perusse, Louis and van Rooij, Frank J A and Xiang, Yong-Bing and Wen, Wanqing and Wojczynski, Mary K and Zhu, Jingwen and Borecki, Ingrid B and Bouchard, Claude and Cai, Qiuyin and Cooper, Cyrus and Dedoussis, George V and Deloukas, Panos and Ferrucci, Luigi and Forouhi, Nita G and Hansen, Torben and Christiansen, Lene and Hofman, Albert and Johansson, Ingegerd and J{\o}rgensen, Torben and Karasawa, Shigeru and Khaw, Kay-Tee and Kim, Mi-Kyung and Kristiansson, Kati and Li, Huaixing and Lin, Xu and Liu, Yongmei and Lohman, Kurt K and Long, Jirong and Mikkil{\"a}, Vera and Mozaffarian, Dariush and North, Kari and Pedersen, Oluf and Raitakari, Olli and Rissanen, Harri and Tuomilehto, Jaakko and van der Schouw, Yvonne T and Uitterlinden, Andr{\'e} G and Zillikens, M Carola and Franco, Oscar H and Shyong Tai, E and Ou Shu, Xiao and Siscovick, David S and Toft, Ulla and Verschuren, W M Monique and Vollenweider, Peter and Wareham, Nicholas J and Witteman, Jacqueline C M and Zheng, Wei and Ridker, Paul M and Kang, Jae H and Liang, Liming and Jensen, Majken K and Curhan, Gary C and Pasquale, Louis R and Hunter, David J and Mohlke, Karen L and Uusitupa, Matti and Cupples, L Adrienne and Rankinen, Tuomo and Orho-Melander, Marju and Wang, Tao and Chasman, Daniel I and Franks, Paul W and S{\o}rensen, Thorkild I A and Hu, Frank B and Loos, Ruth J F and Nettleton, Jennifer A and Qi, Lu} } @article {6567, title = {Genome-wide association study of plasma N6 polyunsaturated fatty acids within the cohorts for heart and aging research in genomic epidemiology consortium.}, journal = {Circ Cardiovasc Genet}, volume = {7}, year = {2014}, month = {2014 Jun}, pages = {321-331}, abstract = {

BACKGROUND: Omega6 (n6) polyunsaturated fatty acids (PUFAs) and their metabolites are involved in cell signaling, inflammation, clot formation, and other crucial biological processes. Genetic components, such as variants of fatty acid desaturase (FADS) genes, determine the composition of n6 PUFAs.

METHODS AND RESULTS: To elucidate undiscovered biological pathways that may influence n6 PUFA composition, we conducted genome-wide association studies and meta-analyses of associations of common genetic variants with 6 plasma n6 PUFAs in 8631 white adults (55\% women) across 5 prospective studies. Plasma phospholipid or total plasma fatty acids were analyzed by similar gas chromatography techniques. The n6 fatty acids linoleic acid (LA), γ-linolenic acid (GLA), dihomo-GLA, arachidonic acid, and adrenic acid were expressed as percentage of total fatty acids. We performed linear regression with robust SEs to test for single-nucleotide polymorphism-fatty acid associations, with pooling using inverse-variance-weighted meta-analysis. Novel regions were identified on chromosome 10 associated with LA (rs10740118; P=8.1{\texttimes}10(-9); near NRBF2), on chromosome 16 with LA, GLA, dihomo-GLA, and arachidonic acid (rs16966952; P=1.2{\texttimes}10(-15), 5.0{\texttimes}10(-11), 7.6{\texttimes}10(-65), and 2.4{\texttimes}10(-10), respectively; NTAN1), and on chromosome 6 with adrenic acid after adjustment for arachidonic acid (rs3134950; P=2.1{\texttimes}10(-10); AGPAT1). We confirmed previous findings of the FADS cluster on chromosome 11 with LA and arachidonic acid, and further observed novel genome-wide significant association of this cluster with GLA, dihomo-GLA, and adrenic acid (P=2.3{\texttimes}10(-72), 2.6{\texttimes}10(-151), and 6.3{\texttimes}10(-140), respectively).

CONCLUSIONS: Our findings suggest that along with the FADS gene cluster, additional genes may influence n6 PUFA composition.

}, keywords = {Adult, Aged, Aged, 80 and over, Aging, Chromosomes, Human, Pair 10, Chromosomes, Human, Pair 16, Chromosomes, Human, Pair 6, Fatty Acid Desaturases, Fatty Acids, Omega-6, Female, Genome-Wide Association Study, Genomics, Heart Diseases, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Prospective Studies, Sequence Analysis, DNA}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.113.000208}, author = {Guan, Weihua and Steffen, Brian T and Lemaitre, Rozenn N and Wu, Jason H Y and Tanaka, Toshiko and Manichaikul, Ani and Foy, Millennia and Rich, Stephen S and Wang, Lu and Nettleton, Jennifer A and Tang, Weihong and Gu, Xiangjun and Bandinelli, Stafania and King, Irena B and McKnight, Barbara and Psaty, Bruce M and Siscovick, David and Djouss{\'e}, Luc and Chen, Yii-Der Ida and Ferrucci, Luigi and Fornage, Myriam and Mozafarrian, Dariush and Tsai, Michael Y and Steffen, Lyn M} } @article {6844, title = {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.}, journal = {Am J Clin Nutr}, volume = {102}, year = {2015}, month = {2015 Nov}, pages = {1266-78}, abstract = {

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).

}, keywords = {Blood Glucose, Cohort Studies, Genetic Association Studies, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Hyperglycemia, Hyperinsulinism, Insulin, Insulin Resistance, Insulin-Secreting Cells, Meat, Meat Products, Middle Aged, Polymorphism, Single Nucleotide, Risk Factors}, issn = {1938-3207}, doi = {10.3945/ajcn.114.101238}, author = {Fretts, Amanda M and Follis, Jack L and Nettleton, Jennifer A and Lemaitre, Rozenn N and Ngwa, Julius S and Wojczynski, Mary K and Kalafati, Ioanna Panagiota and Varga, Tibor V and Frazier-Wood, Alexis C and Houston, Denise K and Lahti, Jari and Ericson, Ulrika and van den Hooven, Edith H and Mikkil{\"a}, Vera and Kiefte-de Jong, Jessica C and Mozaffarian, Dariush and Rice, Kenneth and Renstrom, Frida and North, Kari E and McKeown, Nicola M and Feitosa, Mary F and Kanoni, Stavroula and Smith, Caren E and Garcia, Melissa E and Tiainen, Anna-Maija and Sonestedt, Emily and Manichaikul, Ani and van Rooij, Frank J A and Dimitriou, Maria and Raitakari, Olli and Pankow, James S and Djouss{\'e}, Luc and Province, Michael A and Hu, Frank B and Lai, Chao-Qiang and Keller, Margaux F and Per{\"a}l{\"a}, Mia-Maria and Rotter, Jerome I and Hofman, Albert and Graff, Misa and K{\"a}h{\"o}nen, Mika and Mukamal, Kenneth and Johansson, Ingegerd and Ordovas, Jose M and Liu, Yongmei and M{\"a}nnist{\"o}, Satu and Uitterlinden, Andr{\'e} G and Deloukas, Panos and Sepp{\"a}l{\"a}, Ilkka and Psaty, Bruce M and Cupples, L Adrienne and Borecki, Ingrid B and Franks, Paul W and Arnett, Donna K and Nalls, Mike A and Eriksson, Johan G and Orho-Melander, Marju and Franco, Oscar H and Lehtim{\"a}ki, Terho and Dedoussis, George V and Meigs, James B and Siscovick, David S} } @article {6687, title = {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.}, journal = {Mol Nutr Food Res}, volume = {59}, year = {2015}, month = {2015 Jul}, pages = {1373-83}, abstract = {

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.

}, keywords = {Acetyltransferases, Acyltransferases, Adaptor Proteins, Signal Transducing, Carboxy-Lyases, Diet, Docosahexaenoic Acids, Eicosapentaenoic Acid, Erythrocyte Membrane, Fatty Acid Desaturases, Fatty Acids, Fatty Acids, Omega-3, Female, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide}, issn = {1613-4133}, doi = {10.1002/mnfr.201400734}, author = {Smith, Caren E and Follis, Jack L and Nettleton, Jennifer A and Foy, Millennia and Wu, Jason H Y and Ma, Yiyi and Tanaka, Toshiko and Manichakul, Ani W and Wu, Hongyu and Chu, Audrey Y and Steffen, Lyn M and Fornage, Myriam and Mozaffarian, Dariush and Kabagambe, Edmond K and Ferruci, Luigi and Chen, Yii-Der Ida and Rich, Stephen S and Djouss{\'e}, Luc and Ridker, Paul M and Tang, Weihong and McKnight, Barbara and Tsai, Michael Y and Bandinelli, Stefania and Rotter, Jerome I and Hu, Frank B and Chasman, Daniel I and Psaty, Bruce M and Arnett, Donna K and King, Irena B and Sun, Qi and Wang, Lu and Lumley, Thomas and Chiuve, Stephanie E and Siscovick, David S and Ordovas, Jose M and Lemaitre, Rozenn N} } @article {6802, title = {Gene {\texttimes} dietary pattern interactions in obesity: analysis of up to 68 317 adults of European ancestry.}, journal = {Hum Mol Genet}, volume = {24}, year = {2015}, month = {2015 Aug 15}, pages = {4728-38}, abstract = {

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.

}, keywords = {Adult, Body Mass Index, Case-Control Studies, Diet, Western, Epistasis, Genetic, European Continental Ancestry Group, Female, Genetic Loci, Genome-Wide Association Study, Humans, Male, Obesity, Polymorphism, Single Nucleotide}, issn = {1460-2083}, doi = {10.1093/hmg/ddv186}, author = {Nettleton, Jennifer A and Follis, Jack L and Ngwa, Julius S and Smith, Caren E and Ahmad, Shafqat and Tanaka, Toshiko and Wojczynski, Mary K and Voortman, Trudy and Lemaitre, Rozenn N and Kristiansson, Kati and Nuotio, Marja-Liisa and Houston, Denise K and Per{\"a}l{\"a}, Mia-Maria and Qi, Qibin and Sonestedt, Emily and Manichaikul, Ani and Kanoni, Stavroula and Ganna, Andrea and Mikkil{\"a}, Vera and North, Kari E and Siscovick, David S and Harald, Kennet and McKeown, Nicola M and Johansson, Ingegerd and Rissanen, Harri and Liu, Yongmei and Lahti, Jari and Hu, Frank B and Bandinelli, Stefania and Rukh, Gull and Rich, Stephen and Booij, Lisanne and Dmitriou, Maria and Ax, Erika and Raitakari, Olli and Mukamal, Kenneth and M{\"a}nnist{\"o}, Satu and Hallmans, G{\"o}ran and Jula, Antti and Ericson, Ulrika and Jacobs, David R and van Rooij, Frank J A and Deloukas, Panos and Sjogren, Per and K{\"a}h{\"o}nen, Mika and Djouss{\'e}, Luc and Perola, Markus and Barroso, In{\^e}s and Hofman, Albert and Stirrups, Kathleen and Viikari, Jorma and Uitterlinden, Andr{\'e} G and Kalafati, Ioanna P and Franco, Oscar H and Mozaffarian, Dariush and Salomaa, Veikko and Borecki, Ingrid B and Knekt, Paul and Kritchevsky, Stephen B and Eriksson, Johan G and Dedoussis, George V and Qi, Lu and Ferrucci, Luigi and Orho-Melander, Marju and Zillikens, M Carola and Ingelsson, Erik and Lehtim{\"a}ki, Terho and Renstrom, Frida and Cupples, L Adrienne and Loos, Ruth J F and Franks, Paul W} } @article {7578, title = {Genome-wide association meta-analysis of fish and EPA+DHA consumption in 17 US and European cohorts.}, journal = {PLoS One}, volume = {12}, year = {2017}, month = {2017}, pages = {e0186456}, abstract = {

BACKGROUND: Regular fish and omega-3 consumption may have several health benefits and are recommended by major dietary guidelines. Yet, their intakes remain remarkably variable both within and across populations, which could partly owe to genetic influences.

OBJECTIVE: To identify common genetic variants that influence fish and dietary eicosapentaenoic acid plus docosahexaenoic acid (EPA+DHA) consumption.

DESIGN: We conducted genome-wide association (GWA) meta-analysis of fish (n = 86,467) and EPA+DHA (n = 62,265) consumption in 17 cohorts of European descent from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Nutrition Working Group. Results from cohort-specific GWA analyses (additive model) for fish and EPA+DHA consumption were adjusted for age, sex, energy intake, and population stratification, and meta-analyzed separately using fixed-effect meta-analysis with inverse variance weights (METAL software). Additionally, heritability was estimated in 2 cohorts.

RESULTS: Heritability estimates for fish and EPA+DHA consumption ranged from 0.13-0.24 and 0.12-0.22, respectively. A significant GWA for fish intake was observed for rs9502823 on chromosome 6: each copy of the minor allele (FreqA = 0.015) was associated with 0.029 servings/day (~1 serving/month) lower fish consumption (P = 1.96x10-8). No significant association was observed for EPA+DHA, although rs7206790 in the obesity-associated FTO gene was among top hits (P = 8.18x10-7). Post-hoc calculations demonstrated 95\% statistical power to detect a genetic variant associated with effect size of 0.05\% for fish and 0.08\% for EPA+DHA.

CONCLUSIONS: These novel findings suggest that non-genetic personal and environmental factors are principal determinants of the remarkable variation in fish consumption, representing modifiable targets for increasing intakes among all individuals. Genes underlying the signal at rs72838923 and mechanisms for the association warrant further investigation.

}, keywords = {Adult, Aged, Cohort Studies, Docosahexaenoic Acids, Eicosapentaenoic Acid, Europe, European Continental Ancestry Group, Female, Genome-Wide Association Study, Humans, Male, Middle Aged, Seafood, United States}, issn = {1932-6203}, doi = {10.1371/journal.pone.0186456}, author = {Mozaffarian, Dariush and Dashti, Hassan S and Wojczynski, Mary K and Chu, Audrey Y and Nettleton, Jennifer A and M{\"a}nnist{\"o}, Satu and Kristiansson, Kati and Reedik, M{\"a}gi and Lahti, Jari and Houston, Denise K and Cornelis, Marilyn C and van Rooij, Frank J A and Dimitriou, Maria and Kanoni, Stavroula and Mikkil{\"a}, Vera and Steffen, Lyn M and de Oliveira Otto, Marcia C and Qi, Lu and Psaty, Bruce and Djouss{\'e}, Luc and Rotter, Jerome I and Harald, Kennet and Perola, Markus and Rissanen, Harri and Jula, Antti and Krista, Fischer and Mihailov, Evelin and Feitosa, Mary F and Ngwa, Julius S and Xue, Luting and Jacques, Paul F and Per{\"a}l{\"a}, Mia-Maria and Palotie, Aarno and Liu, Yongmei and Nalls, Nike A and Ferrucci, Luigi and Hernandez, Dena and Manichaikul, Ani and Tsai, Michael Y and Kiefte-de Jong, Jessica C and Hofman, Albert and Uitterlinden, Andr{\'e} G and Rallidis, Loukianos and Ridker, Paul M and Rose, Lynda M and Buring, Julie E and Lehtim{\"a}ki, Terho and K{\"a}h{\"o}nen, Mika and Viikari, Jorma and Lemaitre, Rozenn and Salomaa, Veikko and Knekt, Paul and Metspalu, Andres and Borecki, Ingrid B and Cupples, L Adrienne and Eriksson, Johan G and Kritchevsky, Stephen B and Bandinelli, Stefania and Siscovick, David and Franco, Oscar H and Deloukas, Panos and Dedoussis, George and Chasman, Daniel I and Raitakari, Olli and Tanaka, Toshiko} }