@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 {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 {6927, title = {Gene-Environment Interactions of Circadian-Related Genes for Cardiometabolic Traits.}, journal = {Diabetes Care}, volume = {38}, year = {2015}, month = {2015 Aug}, pages = {1456-66}, abstract = {

OBJECTIVE: Common circadian-related gene variants associate with increased risk for metabolic alterations including type 2 diabetes. However, little is known about whether diet and sleep could modify associations between circadian-related variants (CLOCK-rs1801260, CRY2-rs11605924, MTNR1B-rs1387153, MTNR1B-rs10830963, NR1D1-rs2314339) and cardiometabolic traits (fasting glucose [FG], HOMA-insulin resistance, BMI, waist circumference, and HDL-cholesterol) to facilitate personalized recommendations.

RESEARCH DESIGN AND METHODS: We conducted inverse-variance weighted, fixed-effect meta-analyses of results of adjusted associations and interactions between dietary intake/sleep duration and selected variants on cardiometabolic traits from 15 cohort studies including up to 28,190 participants of European descent from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium.

RESULTS: We observed significant associations between relative macronutrient intakes and glycemic traits and short sleep duration (<7 h) and higher FG and replicated known MTNR1B associations with glycemic traits. No interactions were evident after accounting for multiple comparisons. However, we observed nominally significant interactions (all P < 0.01) between carbohydrate intake and MTNR1B-rs1387153 for FG with a 0.003 mmol/L higher FG with each additional 1\% carbohydrate intake in the presence of the T allele, between sleep duration and CRY2-rs11605924 for HDL-cholesterol with a 0.010 mmol/L higher HDL-cholesterol with each additional hour of sleep in the presence of the A allele, and between long sleep duration (>=9 h) and MTNR1B-rs1387153 for BMI with a 0.60 kg/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{\textemdash}specifically higher carbohydrate and lower fat composition{\textemdash}and normal sleep duration should continue to be emphasized among individuals with the investigated circadian-related gene variants.

}, keywords = {Adult, Alleles, Blood Glucose, Circadian Rhythm Signaling Peptides and Proteins, Cohort Studies, Diabetes Mellitus, Type 2, Diet, Fat-Restricted, European Continental Ancestry Group, Fasting, Female, Gene-Environment Interaction, Humans, Insulin Resistance, Male, Middle Aged, Multicenter Studies as Topic, Observational Studies as Topic, Phenotype, Polymorphism, Single Nucleotide, Sleep, Waist Circumference}, issn = {1935-5548}, doi = {10.2337/dc14-2709}, author = {Dashti, Hassan S and Follis, Jack L and Smith, Caren E and Tanaka, Toshiko and Garaulet, Marta and Gottlieb, Daniel J and Hruby, Adela and Jacques, Paul F and Kiefte-de Jong, Jessica C and Lamon-Fava, Stefania and Scheer, Frank A J L and Bartz, Traci M and Kovanen, Leena and Wojczynski, Mary K and Frazier-Wood, Alexis C and Ahluwalia, Tarunveer S and Per{\"a}l{\"a}, Mia-Maria and Jonsson, Anna and Muka, Taulant and Kalafati, Ioanna P and Mikkil{\"a}, Vera and Ordovas, Jose M} } @article {6614, title = {Habitual sleep duration is associated with BMI and macronutrient intake and may be modified by CLOCK genetic variants.}, journal = {Am J Clin Nutr}, volume = {101}, year = {2015}, month = {2015 Jan}, pages = {135-43}, abstract = {

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 {\textpm} SE = 0.16 {\textpm} 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 {\textpm} 0.06\%, P = 0.03; women: 0.10 {\textpm} 0.05\%, P = 0.04) and with lower carbohydrate (-0.31 {\textpm} 0.12\%, P < 0.01), higher total fat (0.18 {\textpm} 0.09\%, P = 0.05), and higher PUFA (0.05 {\textpm} 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.

}, keywords = {Adult, Body Mass Index, CLOCK Proteins, Cohort Studies, Cross-Sectional Studies, Diet, Dietary Proteins, Energy Intake, European Continental Ancestry Group, Fatty Acids, Unsaturated, Female, Gene-Environment Interaction, Genetic Predisposition to Disease, Humans, Male, Middle Aged, Obesity, Polymorphism, Single Nucleotide, Sleep, Young Adult}, issn = {1938-3207}, doi = {10.3945/ajcn.114.095026}, author = {Dashti, Hassan S and Follis, Jack L and Smith, Caren E and Tanaka, Toshiko and Cade, Brian E and Gottlieb, Daniel J and Hruby, Adela and Jacques, Paul F and Lamon-Fava, Stefania and Richardson, Kris and Saxena, Richa and Scheer, Frank A J L and Kovanen, Leena and Bartz, Traci M and Per{\"a}l{\"a}, Mia-Maria and Jonsson, Anna and Frazier-Wood, Alexis C and Kalafati, Ioanna-Panagiota and Mikkil{\"a}, Vera and Partonen, Timo and Lemaitre, Rozenn N and Lahti, Jari and Hernandez, Dena G and Toft, Ulla and Johnson, W Craig and Kanoni, Stavroula and Raitakari, Olli T and Perola, Markus and Psaty, Bruce M and Ferrucci, Luigi and Grarup, Niels and Highland, Heather M and Rallidis, Loukianos and K{\"a}h{\"o}nen, Mika and Havulinna, Aki S and Siscovick, David S and R{\"a}ikk{\"o}nen, Katri and J{\o}rgensen, Torben and Rotter, Jerome I and Deloukas, Panos and Viikari, Jorma S A and Mozaffarian, Dariush and Linneberg, Allan and Sepp{\"a}l{\"a}, Ilkka and Hansen, Torben and Salomaa, Veikko and Gharib, Sina A and Eriksson, Johan G and Bandinelli, Stefania and Pedersen, Oluf and Rich, Stephen S and Dedoussis, George and Lehtim{\"a}ki, Terho and Ordovas, Jose M} } @article {7346, title = {Discovery and fine-mapping of loci associated with monounsaturated fatty acids through trans-ethnic meta-analysis in Chinese and European populations.}, journal = {J Lipid Res}, year = {2017}, month = {2017 Mar 15}, abstract = {

Monounsaturated fatty acids (MUFAs) are unsaturated fatty acids with one double bond and are derived from endogenous synthesis and dietary intake. Accumulating evidence has suggested that plasma and erythrocyte MUFA levels were associated with cardiometabolic disorders including cardiovascular disease (CVD), type 2 diabetes (T2D) and metabolic syndrome (MS). Previous genome-wide association studies (GWAS) have identified seven loci for plasma and erythrocyte palmitoleic acid and oleic acid levels in populations of European origin. To identify additional MUFA-associated loci and the potential causal variant at each locus, we performed ethnic-specific GWAS meta-analyses and trans-ethnic meta-analyses in over 15,000 participants of Chinese- and European-ancestry. We identified novel genome-wide significant associations for vaccenic acid at FADS1/2 and PKD2L1 [log10(Bayes factor)>=8.07] and for gondoic acid at FADS1/2 and GCKR [log10(Bayes factor)>=61619;6.22], and also observed improved fine-mapping resolutions at FADS1/2 and GCKR loci. The greatest improvement was observed at GCKR, where the number of variants in the 99\% credible set was reduced from 16 (covering ~95kb) to five (covering ~20kb, including a missense variant rs1260326) after trans-ethnic meta-analysis. We also confirmed the previously reported associations of PKD2L1, FADS1/2, GCKR and HIF1AN with palmitoleic acid and of FADS1/2 and LPCAT3 with oleic acid in the Chinese-specific GWAS and trans-ethnic meta-analyses. Pathway-based analyses suggested that the identified loci were enriched in unsaturated fatty acids metabolism and signaling pathways. Our findings provided novel insight into the genetic basis relevant to MUFA metabolism and biology.

}, issn = {1539-7262}, doi = {10.1194/jlr.P071860}, author = {Hu, Yao and Tanaka, Toshiko and Zhu, Jingwen and Guan, Weihua and Wu, Jason H Y and Psaty, Bruce M and McKnight, Barbara and King, Irena B and Sun, Qi and Richard, Melissa and Manichaikul, Ani and Frazier-Wood, Alexis C and Kabagambe, Edmond K and Hopkins, Paul N and Ordovas, Jose M and Ferrucci, Luigi and Bandinelli, Stefania and Arnett, Donna K and Chen, Yii-der I and Liang, Shuang and Siscovick, David S and Tsai, Michael Y and Rich, Stephen S and Fornage, Myriam and Hu, Frank B and Rimm, Eric B and Jensen, Majken K and Lemaitre, Rozenn N and Mozaffarian, Dariush and Steffen, Lyn M and Morris, Andrew P and Li, Huaixing and Lin, Xu} } @article {7588, title = {Genome-Wide Interactions with Dairy Intake for Body Mass Index in Adults of European Descent.}, journal = {Mol Nutr Food Res}, year = {2017}, month = {2017 Sep 21}, abstract = {

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{\textquoteright} of LINC00333) was replicated (p-interaction = 0.004). In the discovery cohorts, rs9635058 interacted with dairy (p-interaction = 7.36 {\texttimes} 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.

}, issn = {1613-4133}, doi = {10.1002/mnfr.201700347}, author = {Smith, Caren E and Follis, Jack L and Dashti, Hassan S and Tanaka, Toshiko and Graff, Mariaelisa and Fretts, Amanda M and Kilpel{\"a}inen, Tuomas O and Wojczynski, Mary K and Richardson, Kris and Nalls, Mike A and Schulz, Christina-Alexandra and Liu, Yongmei and Frazier-Wood, Alexis C and van Eekelen, Esther and Wang, Carol and de Vries, Paul S and Mikkil{\"a}, Vera and Rohde, Rebecca and Psaty, Bruce M and Hansen, Torben and Feitosa, Mary F and Lai, Chao-Qiang and Houston, Denise K and Ferruci, Luigi and Ericson, Ulrika and Wang, Zhe and de Mutsert, Ren{\'e}e and Oddy, Wendy H and de Jonge, Ester A L and Sepp{\"a}l{\"a}, Ilkka and Justice, Anne E and Lemaitre, Rozenn N and S{\o}rensen, Thorkild I A and Province, Michael A and Parnell, Laurence D and Garcia, Melissa E and Bandinelli, Stefania and Orho-Melander, Marju and Rich, Stephen S and Rosendaal, Frits R and Pennell, Craig E and Kiefte-de Jong, Jessica C and K{\"a}h{\"o}nen, Mika and Young, Kristin L and Pedersen, Oluf and Aslibekyan, Stella and Rotter, Jerome I and Mook-Kanamori, Dennis O and Zillikens, M Carola and Raitakari, Olli T and North, Kari E and Overvad, Kim and Arnett, Donna K and Hofman, Albert and Lehtim{\"a}ki, Terho and Tj{\o}nneland, Anne and Uitterlinden, Andr{\'e} G and Rivadeneira, Fernando and Franco, Oscar H and German, J Bruce and Siscovick, David S and Cupples, L Adrienne and Ordovas, Jose M} } @article {8041, title = {Fatty acid biomarkers of dairy fat consumption and incidence of type 2 diabetes: A pooled analysis of prospective cohort studies.}, journal = {PLoS Med}, volume = {15}, year = {2018}, month = {2018 10}, pages = {e1002670}, abstract = {

BACKGROUND: We aimed to investigate prospective associations of circulating or adipose tissue odd-chain fatty acids 15:0 and 17:0 and trans-palmitoleic acid, t16:1n-7, as potential biomarkers of dairy fat intake, with incident type 2 diabetes (T2D).

METHODS AND FINDINGS: Sixteen prospective cohorts from 12 countries (7 from the United States, 7 from Europe, 1 from Australia, 1 from Taiwan) performed new harmonised individual-level analysis for the prospective associations according to a standardised plan. In total, 63,682 participants with a broad range of baseline ages and BMIs and 15,180 incident cases of T2D over the average of 9 years of follow-up were evaluated. Study-specific results were pooled using inverse-variance-weighted meta-analysis. Prespecified interactions by age, sex, BMI, and race/ethnicity were explored in each cohort and were meta-analysed. Potential heterogeneity by cohort-specific characteristics (regions, lipid compartments used for fatty acid assays) was assessed with metaregression. After adjustment for potential confounders, including measures of adiposity (BMI, waist circumference) and lipogenesis (levels of palmitate, triglycerides), higher levels of 15:0, 17:0, and t16:1n-7 were associated with lower incidence of T2D. In the most adjusted model, the hazard ratio (95\% CI) for incident T2D per cohort-specific 10th to 90th percentile range of 15:0 was 0.80 (0.73-0.87); of 17:0, 0.65 (0.59-0.72); of t16:1n7, 0.82 (0.70-0.96); and of their sum, 0.71 (0.63-0.79). In exploratory analyses, similar associations for 15:0, 17:0, and the sum of all three fatty acids were present in both genders but stronger in women than in men (pinteraction < 0.001). Whereas studying associations with biomarkers has several advantages, as limitations, the biomarkers do not distinguish between different food sources of dairy fat (e.g., cheese, yogurt, milk), and residual confounding by unmeasured or imprecisely measured confounders may exist.

CONCLUSIONS: In a large meta-analysis that pooled the findings from 16 prospective cohort studies, higher levels of 15:0, 17:0, and t16:1n-7 were associated with a lower risk of T2D.

}, keywords = {Aged, Australia, Biomarkers, Dairy Products, Diabetes Mellitus, Type 2, Dietary Fats, Europe, Fatty Acids, Fatty Acids, Monounsaturated, Female, Humans, Incidence, Male, Middle Aged, Prospective Studies, Sex Factors, Taiwan, United States}, issn = {1549-1676}, doi = {10.1371/journal.pmed.1002670}, author = {Imamura, Fumiaki and Fretts, Amanda and Marklund, Matti and Ardisson Korat, Andres V and Yang, Wei-Sin and Lankinen, Maria and Qureshi, Waqas and Helmer, Catherine and Chen, Tzu-An and Wong, Kerry and Bassett, Julie K and Murphy, Rachel and Tintle, Nathan and Yu, Chaoyu Ian and Brouwer, Ingeborg A and Chien, Kuo-Liong and Frazier-Wood, Alexis C and Del Gobbo, Liana C and Djouss{\'e}, Luc and Geleijnse, Johanna M and Giles, Graham G and de Goede, Janette and Gudnason, Vilmundur and Harris, William S and Hodge, Allison and Hu, Frank and Koulman, Albert and Laakso, Markku and Lind, Lars and Lin, Hung-Ju and McKnight, Barbara and Rajaobelina, Kalina and Riserus, Ulf and Robinson, Jennifer G and Samieri, Cecilia and Siscovick, David S and Soedamah-Muthu, Sabita S and Sotoodehnia, Nona and Sun, Qi and Tsai, Michael Y and Uusitupa, Matti and Wagenknecht, Lynne E and Wareham, Nick J and Wu, Jason HY and Micha, Renata and Forouhi, Nita G and Lemaitre, Rozenn N and Mozaffarian, Dariush} } @article {7775, title = {Meta-analysis across Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium provides evidence for an association of serum vitamin D with pulmonary function.}, journal = {Br J Nutr}, year = {2018}, month = {2018 Sep 12}, pages = {1-12}, abstract = {

The role that vitamin D plays in pulmonary function remains uncertain. Epidemiological studies reported mixed findings for serum 25-hydroxyvitamin D (25(OH)D)-pulmonary function association. We conducted the largest cross-sectional meta-analysis of the 25(OH)D-pulmonary function association to date, based on nine European ancestry (EA) cohorts (n 22 838) and five African ancestry (AA) cohorts (n 4290) in the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium. Data were analysed using linear models by cohort and ancestry. Effect modification by smoking status (current/former/never) was tested. Results were combined using fixed-effects meta-analysis. Mean serum 25(OH)D was 68 (sd 29) nmol/l for EA and 49 (sd 21) nmol/l for AA. For each 1 nmol/l higher 25(OH)D, forced expiratory volume in the 1st second (FEV1) was higher by 1{\textperiodcentered}1 ml in EA (95 \% CI 0{\textperiodcentered}9, 1{\textperiodcentered}3; P<0{\textperiodcentered}0001) and 1{\textperiodcentered}8 ml (95 \% CI 1{\textperiodcentered}1, 2{\textperiodcentered}5; P<0{\textperiodcentered}0001) in AA (P race difference=0{\textperiodcentered}06), and forced vital capacity (FVC) was higher by 1{\textperiodcentered}3 ml in EA (95 \% CI 1{\textperiodcentered}0, 1{\textperiodcentered}6; P<0{\textperiodcentered}0001) and 1{\textperiodcentered}5 ml (95 \% CI 0{\textperiodcentered}8, 2{\textperiodcentered}3; P=0{\textperiodcentered}0001) in AA (P race difference=0{\textperiodcentered}56). Among EA, the 25(OH)D-FVC association was stronger in smokers: per 1 nmol/l higher 25(OH)D, FVC was higher by 1{\textperiodcentered}7 ml (95 \% CI 1{\textperiodcentered}1, 2{\textperiodcentered}3) for current smokers and 1{\textperiodcentered}7 ml (95 \% CI 1{\textperiodcentered}2, 2{\textperiodcentered}1) for former smokers, compared with 0{\textperiodcentered}8 ml (95 \% CI 0{\textperiodcentered}4, 1{\textperiodcentered}2) for never smokers. In summary, the 25(OH)D associations with FEV1 and FVC were positive in both ancestries. In EA, a stronger association was observed for smokers compared with never smokers, which supports the importance of vitamin D in vulnerable populations.

}, issn = {1475-2662}, doi = {10.1017/S0007114518002180}, author = {Xu, Jiayi and Bartz, Traci M and Chittoor, Geetha and Eiriksdottir, Gudny and Manichaikul, Ani W and Sun, Fangui and Terzikhan, Natalie and Zhou, Xia and Booth, Sarah L and Brusselle, Guy G and de Boer, Ian H and Fornage, Myriam and Frazier-Wood, Alexis C and Graff, Mariaelisa and Gudnason, Vilmundur and Harris, Tamara B and Hofman, Albert and Hou, Ruixue and Houston, Denise K and Jacobs, David R and Kritchevsky, Stephen B and Latourelle, Jeanne and Lemaitre, Rozenn N and Lutsey, Pamela L and O{\textquoteright}Connor, George and Oelsner, Elizabeth C and Pankow, James S and Psaty, Bruce M and Rohde, Rebecca R and Rich, Stephen S and Rotter, Jerome I and Smith, Lewis J and Stricker, Bruno H and Voruganti, V Saroja and Wang, Thomas J and Zillikens, M Carola and Barr, R Graham and Dupuis, Jos{\'e}e and Gharib, Sina A and Lahousse, Lies and London, Stephanie J and North, Kari E and Smith, Albert V and Steffen, Lyn M and Hancock, Dana B and Cassano, Patricia A} } @article {7675, title = {Multiethnic Meta-Analysis Identifies RAI1 as a Possible Obstructive Sleep Apnea-related Quantitative Trait Locus in Men.}, journal = {Am J Respir Cell Mol Biol}, volume = {58}, year = {2018}, month = {2018 Mar}, pages = {391-401}, abstract = {

Obstructive sleep apnea (OSA) is a common heritable disorder displaying marked sexual dimorphism in disease prevalence and progression. Previous genetic association studies have identified a few genetic loci associated with OSA and related quantitative traits, but they have only focused on single ethnic groups, and a large proportion of the heritability remains unexplained. The apnea-hypopnea index (AHI) is a commonly used quantitative measure characterizing OSA severity. Because OSA differs by sex, and the pathophysiology of obstructive events differ in rapid eye movement (REM) and non-REM (NREM) sleep, we hypothesized that additional genetic association signals would be identified by analyzing the NREM/REM-specific AHI and by conducting sex-specific analyses in multiethnic samples. We performed genome-wide association tests for up to 19,733 participants of African, Asian, European, and Hispanic/Latino American ancestry in 7 studies. We identified rs12936587 on chromosome 17 as a possible quantitative trait locus for NREM AHI in men (N = 6,737; P = 1.7 {\texttimes} 10) but not in women (P = 0.77). The association with NREM AHI was replicated in a physiological research study (N = 67; P = 0.047). This locus overlapping the RAI1 gene and encompassing genes PEMT1, SREBF1, and RASD1 was previously reported to be associated with coronary artery disease, lipid metabolism, and implicated in Potocki-Lupski syndrome and Smith-Magenis syndrome, which are characterized by abnormal sleep phenotypes. We also identified gene-by-sex interactions in suggestive association regions, suggesting that genetic variants for AHI appear to vary by sex, consistent with the clinical observations of strong sexual dimorphism.

}, issn = {1535-4989}, doi = {10.1165/rcmb.2017-0237OC}, author = {Chen, Han and Cade, Brian E and Gleason, Kevin J and Bjonnes, Andrew C and Stilp, Adrienne M and Sofer, Tamar and Conomos, Matthew P and Ancoli-Israel, Sonia and Arens, Raanan and Azarbarzin, Ali and Bell, Graeme I and Below, Jennifer E and Chun, Sung and Evans, Daniel S and Ewert, Ralf and Frazier-Wood, Alexis C and Gharib, Sina A and Haba-Rubio, Jos{\'e} and Hagen, Erika W and Heinzer, Raphael and Hillman, David R and Johnson, W Craig and Kutalik, Zolt{\'a}n and Lane, Jacqueline M and Larkin, Emma K and Lee, Seung Ku and Liang, Jingjing and Loredo, Jose S and Mukherjee, Sutapa and Palmer, Lyle J and Papanicolaou, George J and Penzel, Thomas and Peppard, Paul E and Post, Wendy S and Ramos, Alberto R and Rice, Ken and Rotter, Jerome I and Sands, Scott A and Shah, Neomi A and Shin, Chol and Stone, Katie L and Stubbe, Beate and Sul, Jae Hoon and Tafti, Mehdi and Taylor, Kent D and Teumer, Alexander and Thornton, Timothy A and Tranah, Gregory J and Wang, Chaolong and Wang, Heming and Warby, Simon C and Wellman, D Andrew and Zee, Phyllis C and Hanis, Craig L and Laurie, Cathy C and Gottlieb, Daniel J and Patel, Sanjay R and Zhu, Xiaofeng and Sunyaev, Shamil R and Saxena, Richa and Lin, Xihong and Redline, Susan} } @article {7576, title = {Sugar-sweetened beverage intake associations with fasting glucose and insulin concentrations are not modified by selected genetic variants in a ChREBP-FGF21 pathway: a meta-analysis.}, journal = {Diabetologia}, volume = {61}, year = {2018}, month = {2018 Feb}, pages = {317-330}, abstract = {

AIMS/HYPOTHESIS: Sugar-sweetened beverages (SSBs) are a major dietary contributor to fructose intake. A molecular pathway involving the carbohydrate responsive element-binding protein (ChREBP) and the metabolic hormone fibroblast growth factor 21 (FGF21) may influence sugar metabolism and, thereby, contribute to fructose-induced metabolic disease. We hypothesise that common variants in 11 genes involved in fructose metabolism and the ChREBP-FGF21 pathway may interact with SSB intake to exacerbate positive associations between higher SSB intake and glycaemic traits.

METHODS: Data from 11 cohorts (six discovery and five replication) in the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium provided association and interaction results from 34,748 adults of European descent. SSB intake (soft drinks, fruit punches, lemonades or other fruit drinks) was derived from food-frequency questionnaires and food diaries. In fixed-effects meta-analyses, we quantified: (1) the associations between SSBs and glycaemic traits (fasting glucose and fasting insulin); and (2) the interactions between SSBs and 18 independent SNPs related to the ChREBP-FGF21 pathway.

RESULTS: In our combined meta-analyses of discovery and replication cohorts, after adjustment for age, sex, energy intake, BMI and other dietary covariates, each additional serving of SSB intake was associated with higher fasting glucose (β~{\textpm}~SE 0.014~{\textpm}~0.004 [mmol/l], p~=~1.5~{\texttimes}~10-3) and higher fasting insulin (0.030~{\textpm}~0.005 [log e pmol/l], p~=~2.0~{\texttimes}~10-10). No significant interactions on glycaemic traits were observed between SSB intake and selected SNPs. While a suggestive interaction was observed in the discovery cohorts with a SNP (rs1542423) in the β-Klotho (KLB) locus on fasting insulin (0.030~{\textpm}~0.011 log e pmol/l, uncorrected p~=~0.006), results in the replication cohorts and combined meta-analyses were non-significant.

CONCLUSIONS/INTERPRETATION: In this large meta-analysis, we observed that SSB intake was associated with higher fasting glucose and insulin. Although a suggestive interaction with a genetic variant in the ChREBP-FGF21 pathway was observed in the discovery cohorts, this observation was not confirmed in the replication analysis.

TRIAL REGISTRATION: Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005121 (Framingham Offspring Study), NCT00005487 (Multi-Ethnic Study of Atherosclerosis) and NCT00005152 (Nurses{\textquoteright} Health Study).

}, issn = {1432-0428}, doi = {10.1007/s00125-017-4475-0}, author = {McKeown, Nicola M and Dashti, Hassan S and Ma, Jiantao and Haslam, Danielle E and Kiefte-de Jong, Jessica C and Smith, Caren E and Tanaka, Toshiko and Graff, Mariaelisa and Lemaitre, Rozenn N and Rybin, Denis and Sonestedt, Emily and Frazier-Wood, Alexis C and Mook-Kanamori, Dennis O and Li, Yanping and Wang, Carol A and Leermakers, Elisabeth T M and Mikkil{\"a}, Vera and Young, Kristin L and Mukamal, Kenneth J and Cupples, L Adrienne and Schulz, Christina-Alexandra and Chen, Tzu-An and Li-Gao, Ruifang and Huang, Tao and Oddy, Wendy H and Raitakari, Olli and Rice, Kenneth and Meigs, James B and Ericson, Ulrika and Steffen, Lyn M and Rosendaal, Frits R and Hofman, Albert and K{\"a}h{\"o}nen, Mika and Psaty, Bruce M and Brunkwall, Louise and Uitterlinden, Andr{\'e} G and Viikari, Jorma and Siscovick, David S and Sepp{\"a}l{\"a}, Ilkka and North, Kari E and Mozaffarian, Dariush and Dupuis, Jos{\'e}e and Orho-Melander, Marju and Rich, Stephen S and de Mutsert, Ren{\'e}e and Qi, Lu and Pennell, Craig E and Franco, Oscar H and Lehtim{\"a}ki, Terho and Herman, Mark A} } @article {8044, title = {Associations of variants In the hexokinase 1 and interleukin 18 receptor regions with oxyhemoglobin saturation during sleep.}, journal = {PLoS Genet}, volume = {15}, year = {2019}, month = {2019 04}, pages = {e1007739}, abstract = {

Sleep disordered breathing (SDB)-related overnight hypoxemia is associated with cardiometabolic disease and other comorbidities. Understanding the genetic bases for variations in nocturnal hypoxemia may help understand mechanisms influencing oxygenation and SDB-related mortality. We conducted genome-wide association tests across 10 cohorts and 4 populations to identify genetic variants associated with three correlated measures of overnight oxyhemoglobin saturation: average and minimum oxyhemoglobin saturation during sleep and the percent of sleep with oxyhemoglobin saturation under 90\%. The discovery sample consisted of 8,326 individuals. Variants with p < 1 {\texttimes} 10(-6) were analyzed in a replication group of 14,410 individuals. We identified 3 significantly associated regions, including 2 regions in multi-ethnic analyses (2q12, 10q22). SNPs in the 2q12 region associated with minimum SpO2 (rs78136548 p = 2.70 {\texttimes} 10(-10)). SNPs at 10q22 were associated with all three traits including average SpO2 (rs72805692 p = 4.58 {\texttimes} 10(-8)). SNPs in both regions were associated in over 20,000 individuals and are supported by prior associations or functional evidence. Four additional significant regions were detected in secondary sex-stratified and combined discovery and replication analyses, including a region overlapping Reelin, a known marker of respiratory complex neurons.These are the first genome-wide significant findings reported for oxyhemoglobin saturation during sleep, a phenotype of high clinical interest. Our replicated associations with HK1 and IL18R1 suggest that variants in inflammatory pathways, such as the biologically-plausible NLRP3 inflammasome, may contribute to nocturnal hypoxemia.

}, keywords = {Adolescent, Adult, Aged, Aged, 80 and over, Cell Adhesion Molecules, Neuronal, Computational Biology, Extracellular Matrix Proteins, Female, Gene Regulatory Networks, Genetic Variation, Genome-Wide Association Study, Hexokinase, Humans, Hypoxia, Interleukin-18 Receptor alpha Subunit, Male, Middle Aged, Nerve Tissue Proteins, NLR Family, Pyrin Domain-Containing 3 Protein, Oxygen, Oxyhemoglobins, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Serine Endopeptidases, Sleep, Sleep Apnea Syndromes, Young Adult}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1007739}, author = {Cade, Brian E and Chen, Han and Stilp, Adrienne M and Louie, Tin and Ancoli-Israel, Sonia and Arens, Raanan and Barfield, Richard and Below, Jennifer E and Cai, Jianwen and Conomos, Matthew P and Evans, Daniel S and Frazier-Wood, Alexis C and Gharib, Sina A and Gleason, Kevin J and Gottlieb, Daniel J and Hillman, David R and Johnson, W Craig and Lederer, David J and Lee, Jiwon and Loredo, Jose S and Mei, Hao and Mukherjee, Sutapa and Patel, Sanjay R and Post, Wendy S and Purcell, Shaun M and Ramos, Alberto R and Reid, Kathryn J and Rice, Ken and Shah, Neomi A and Sofer, Tamar and Taylor, Kent D and Thornton, Timothy A and Wang, Heming and Yaffe, Kristine and Zee, Phyllis C and Hanis, Craig L and Palmer, Lyle J and Rotter, Jerome I and Stone, Katie L and Tranah, Gregory J and Wilson, James G and Sunyaev, Shamil R and Laurie, Cathy C and Zhu, Xiaofeng and Saxena, Richa and Lin, Xihong and Redline, Susan} }