@article {1141, title = {Multiple loci influence erythrocyte phenotypes in the CHARGE Consortium.}, journal = {Nat Genet}, volume = {41}, year = {2009}, month = {2009 Nov}, pages = {1191-8}, abstract = {

Measurements of erythrocytes within the blood are important clinical traits and can indicate various hematological disorders. We report here genome-wide association studies (GWAS) for six erythrocyte traits, including hemoglobin concentration (Hb), hematocrit (Hct), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC) and red blood cell count (RBC). We performed an initial GWAS in cohorts of the CHARGE Consortium totaling 24,167 individuals of European ancestry and replication in additional independent cohorts of the HaemGen Consortium totaling 9,456 individuals. We identified 23 loci significantly associated with these traits in a meta-analysis of the discovery and replication cohorts (combined P values ranging from 5 x 10(-8) to 7 x 10(-86)). Our findings include loci previously associated with these traits (HBS1L-MYB, HFE, TMPRSS6, TFR2, SPTA1) as well as new associations (EPO, TFRC, SH2B3 and 15 other loci). This study has identified new determinants of erythrocyte traits, offering insight into common variants underlying variation in erythrocyte measures.

}, keywords = {Blood Pressure, Cell Line, Cohort Studies, Endothelial Cells, Erythrocytes, Gene Expression, Genome, Human, Genome-Wide Association Study, Humans, Hypertension, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci}, issn = {1546-1718}, doi = {10.1038/ng.466}, author = {Ganesh, Santhi K and Zakai, Neil A and van Rooij, Frank J A and Soranzo, Nicole and Smith, Albert V and Nalls, Michael A and Chen, Ming-Huei and K{\"o}ttgen, Anna and Glazer, Nicole L and Dehghan, Abbas and Kuhnel, Brigitte and Aspelund, Thor and Yang, Qiong and Tanaka, Toshiko and Jaffe, Andrew and Bis, Joshua C M and Verwoert, Germaine C and Teumer, Alexander and Fox, Caroline S and Guralnik, Jack M and Ehret, Georg B and Rice, Kenneth and Felix, Janine F and Rendon, Augusto and Eiriksdottir, Gudny and Levy, Daniel and Patel, Kushang V and Boerwinkle, Eric and Rotter, Jerome I and Hofman, Albert and Sambrook, Jennifer G and Hernandez, Dena G and Zheng, Gang and Bandinelli, Stefania and Singleton, Andrew B and Coresh, Josef and Lumley, Thomas and Uitterlinden, Andr{\'e} G and Vangils, Janine M and Launer, Lenore J and Cupples, L Adrienne and Oostra, Ben A and Zwaginga, Jaap-Jan and Ouwehand, Willem H and Thein, Swee-Lay and Meisinger, Christa and Deloukas, Panos and Nauck, Matthias and Spector, Tim D and Gieger, Christian and Gudnason, Vilmundur and van Duijn, Cornelia M and Psaty, Bruce M and Ferrucci, Luigi and Chakravarti, Aravinda and Greinacher, Andreas and O{\textquoteright}Donnell, Christopher J and Witteman, Jacqueline C M and Furth, Susan and Cushman, Mary and Harris, Tamara B and Lin, Jing-Ping} } @article {1206, title = {Common genetic variants associate with serum phosphorus concentration.}, journal = {J Am Soc Nephrol}, volume = {21}, year = {2010}, month = {2010 Jul}, pages = {1223-32}, abstract = {

Phosphorus is an essential mineral that maintains cellular energy and mineralizes the skeleton. Because complex actions of ion transporters and regulatory hormones regulate serum phosphorus concentrations, genetic variation may determine interindividual variation in phosphorus metabolism. Here, we report a comprehensive genome-wide association study of serum phosphorus concentration. We evaluated 16,264 participants of European ancestry from the Cardiovascular Heath Study, Atherosclerosis Risk in Communities Study, Framingham Offspring Study, and the Rotterdam Study. We excluded participants with an estimated GFR <45 ml/min per 1.73 m(2) to focus on phosphorus metabolism under normal conditions. We imputed genotypes to approximately 2.5 million single-nucleotide polymorphisms in the HapMap and combined study-specific findings using meta-analysis. We tested top polymorphisms from discovery cohorts in a 5444-person replication sample. Polymorphisms in seven loci with minor allele frequencies 0.08 to 0.49 associate with serum phosphorus concentration (P = 3.5 x 10(-16) to 3.6 x 10(-7)). Three loci were near genes encoding the kidney-specific type IIa sodium phosphate co-transporter (SLC34A1), the calcium-sensing receptor (CASR), and fibroblast growth factor 23 (FGF23), proteins that contribute to phosphorus metabolism. We also identified genes encoding phosphatases, kinases, and phosphodiesterases that have yet-undetermined roles in phosphorus homeostasis. In the replication sample, five of seven top polymorphisms associate with serum phosphorous concentrations (P < 0.05 for each). In conclusion, common genetic variants associate with serum phosphorus in the general population. Further study of the loci identified in this study may help elucidate mechanisms of phosphorus regulation.

}, keywords = {Adult, Aged, European Continental Ancestry Group, Female, Fibroblast Growth Factors, Gene Frequency, Genetic Loci, Genetic Variation, Genome-Wide Association Study, Humans, Kidney, Male, Middle Aged, Phosphorus, Polymorphism, Single Nucleotide, Receptors, Calcium-Sensing, Sex Factors, Sodium-Phosphate Cotransporter Proteins, Type IIa}, issn = {1533-3450}, doi = {10.1681/ASN.2009111104}, author = {Kestenbaum, Bryan and Glazer, Nicole L and K{\"o}ttgen, Anna and Felix, Janine F and Hwang, Shih-Jen and Liu, Yongmei and Lohman, Kurt and Kritchevsky, Stephen B and Hausman, Dorothy B and Petersen, Ann-Kristin and Gieger, Christian and Ried, Janina S and Meitinger, Thomas and Strom, Tim M and Wichmann, H Erich and Campbell, Harry and Hayward, Caroline and Rudan, Igor and de Boer, Ian H and Psaty, Bruce M and Rice, Kenneth M and Chen, Yii-Der Ida and Li, Man and Arking, Dan E and Boerwinkle, Eric and Coresh, Josef and Yang, Qiong and Levy, Daniel and van Rooij, Frank J A and Dehghan, Abbas and Rivadeneira, Fernando and Uitterlinden, Andr{\'e} G and Hofman, Albert and van Duijn, Cornelia M and Shlipak, Michael G and Kao, W H Linda and Witteman, Jacqueline C M and Siscovick, David S and Fox, Caroline S} } @article {1223, title = {Genome-wide association studies of serum magnesium, potassium, and sodium concentrations identify six Loci influencing serum magnesium levels.}, journal = {PLoS Genet}, volume = {6}, year = {2010}, month = {2010 Aug 05}, abstract = {

Magnesium, potassium, and sodium, cations commonly measured in serum, are involved in many physiological processes including energy metabolism, nerve and muscle function, signal transduction, and fluid and blood pressure regulation. To evaluate the contribution of common genetic variation to normal physiologic variation in serum concentrations of these cations, we conducted genome-wide association studies of serum magnesium, potassium, and sodium concentrations using approximately 2.5 million genotyped and imputed common single nucleotide polymorphisms (SNPs) in 15,366 participants of European descent from the international CHARGE Consortium. Study-specific results were combined using fixed-effects inverse-variance weighted meta-analysis. SNPs demonstrating genome-wide significant (p<5 x 10(-8)) or suggestive associations (p<4 x 10(-7)) were evaluated for replication in an additional 8,463 subjects of European descent. The association of common variants at six genomic regions (in or near MUC1, ATP2B1, DCDC5, TRPM6, SHROOM3, and MDS1) with serum magnesium levels was genome-wide significant when meta-analyzed with the replication dataset. All initially significant SNPs from the CHARGE Consortium showed nominal association with clinically defined hypomagnesemia, two showed association with kidney function, two with bone mineral density, and one of these also associated with fasting glucose levels. Common variants in CNNM2, a magnesium transporter studied only in model systems to date, as well as in CNNM3 and CNNM4, were also associated with magnesium concentrations in this study. We observed no associations with serum sodium or potassium levels exceeding p<4 x 10(-7). Follow-up studies of newly implicated genomic loci may provide additional insights into the regulation and homeostasis of human serum magnesium levels.

}, keywords = {Adult, Aged, European Continental Ancestry Group, Female, Genome-Wide Association Study, Humans, Magnesium, Male, Middle Aged, Polymorphism, Single Nucleotide, Potassium, Sodium}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1001045}, author = {Meyer, Tamra E and Verwoert, Germaine C and Hwang, Shih-Jen and Glazer, Nicole L and Smith, Albert V and van Rooij, Frank J A and Ehret, Georg B and Boerwinkle, Eric and Felix, Janine F and Leak, Tennille S and Harris, Tamara B and Yang, Qiong and Dehghan, Abbas and Aspelund, Thor and Katz, Ronit and Homuth, Georg and Kocher, Thomas and Rettig, Rainer and Ried, Janina S and Gieger, Christian and Prucha, Hanna and Pfeufer, Arne and Meitinger, Thomas and Coresh, Josef and Hofman, Albert and Sarnak, Mark J and Chen, Yii-Der Ida and Uitterlinden, Andr{\'e} G and Chakravarti, Aravinda and Psaty, Bruce M and van Duijn, Cornelia M and Kao, W H Linda and Witteman, Jacqueline C M and Gudnason, Vilmundur and Siscovick, David S and Fox, Caroline S and K{\"o}ttgen, Anna} } @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 {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 {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 {6573, title = {Trans-ethnic meta-analysis of white blood cell phenotypes.}, journal = {Hum Mol Genet}, volume = {23}, year = {2014}, month = {2014 Dec 20}, pages = {6944-60}, abstract = {

White blood cell (WBC) count is a common clinical measure used as a predictor of certain aspects of human health, including immunity and infection status. WBC count is also a complex trait that varies among individuals and ancestry groups. Differences in linkage disequilibrium structure and heterogeneity in allelic effects are expected to play a role in the associations observed between populations. Prior genome-wide association study (GWAS) meta-analyses have identified genomic loci associated with WBC and its subtypes, but much of the heritability of these phenotypes remains unexplained. Using GWAS summary statistics for over 50 000 individuals from three diverse populations (Japanese, African-American and European ancestry), a Bayesian model methodology was employed to account for heterogeneity between ancestry groups. This approach was used to perform a trans-ethnic meta-analysis of total WBC, neutrophil and monocyte counts. Ten previously known associations were replicated and six new loci were identified, including several regions harboring genes related to inflammation and immune cell function. Ninety-five percent credible interval regions were calculated to narrow the association signals and fine-map the putatively causal variants within loci. Finally, a conditional analysis was performed on the most significant SNPs identified by the trans-ethnic meta-analysis (MA), and nine secondary signals within loci previously associated with WBC or its subtypes were identified. This work illustrates the potential of trans-ethnic analysis and ascribes a critical role to multi-ethnic cohorts and consortia in exploring complex phenotypes with respect to variants that lie outside the European-biased GWAS pool.

}, keywords = {African Americans, Asian Continental Ancestry Group, Bayes Theorem, European Continental Ancestry Group, Genome, Human, Genome-Wide Association Study, Genotype, Humans, Leukocyte Count, Leukocytes, Linkage Disequilibrium, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci}, issn = {1460-2083}, doi = {10.1093/hmg/ddu401}, author = {Keller, Margaux F and Reiner, Alexander P and Okada, Yukinori and van Rooij, Frank J A and Johnson, Andrew D and Chen, Ming-Huei and Smith, Albert V and Morris, Andrew P and Tanaka, Toshiko and Ferrucci, Luigi and Zonderman, Alan B and Lettre, Guillaume and Harris, Tamara and Garcia, Melissa and Bandinelli, Stefania and Qayyum, Rehan and Yanek, Lisa R and Becker, Diane M and Becker, Lewis C and Kooperberg, Charles and Keating, Brendan and Reis, Jared and Tang, Hua and Boerwinkle, Eric and Kamatani, Yoichiro and Matsuda, Koichi and Kamatani, Naoyuki and Nakamura, Yusuke and Kubo, Michiaki and Liu, Simin and Dehghan, Abbas and Felix, Janine F and Hofman, Albert and Uitterlinden, Andr{\'e} G and van Duijn, Cornelia M and Franco, Oscar H and Longo, Dan L and Singleton, Andrew B and Psaty, Bruce M and Evans, Michelle K and Cupples, L Adrienne and Rotter, Jerome I and O{\textquoteright}Donnell, Christopher J and Takahashi, Atsushi and Wilson, James G and Ganesh, Santhi K and Nalls, Mike A} } @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 {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} }