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Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake.

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 × 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 (? ± SE: 0.25 ± 0.04%; P = 1.68 × 10(-8)) and lower fat (? ± SE: -0.21 ± 0.04%; P = 1.57 × 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 (? ± SE: 0.10 ± 0.02%; P = 9.96 × 10(-10)), independent of BMI (after adjustment for BMI, ? ± SE: 0.08 ± 0.02%; P = 3.15 × 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).

SUBMITTER: Tanaka T

PROVIDER: S-EPMC3652928 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature

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Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake.

Tanaka Toshiko T Ngwa Julius S JS van Rooij Frank J A FJ Zillikens M Carola MC Wojczynski Mary K MK Frazier-Wood Alexis C AC Houston Denise K DK Kanoni Stavroula S Lemaitre Rozenn N RN Luan Jian'an J Mikkilä Vera V Renstrom Frida F Sonestedt Emily E Zhao Jing Hua JH Chu Audrey Y AY Qi Lu L Chasman Daniel I DI de Oliveira Otto Marcia C MC Dhurandhar Emily J EJ Feitosa Mary F MF Johansson Ingegerd I Khaw Kay-Tee KT Lohman Kurt K KK Manichaikul Ani A McKeown Nicola M NM Mozaffarian Dariush D Singleton Andrew A Stirrups Kathleen K Viikari Jorma J Ye Zheng Z Bandinelli Stefania S Barroso Inês I Deloukas Panos P Forouhi Nita G NG Hofman Albert A Liu Yongmei Y Lyytikäinen Leo-Pekka LP North Kari E KE Dimitriou Maria M Hallmans Goran G Kähönen Mika M Langenberg Claudia C Ordovas Jose M JM Uitterlinden André G AG Hu Frank B FB Kalafati Ioanna-Panagiota IP Raitakari Olli O Franco Oscar H OH Johnson Andrew A Emilsson Valur V Schrack Jennifer A JA Semba Richard D RD Siscovick David S DS Arnett Donna K DK Borecki Ingrid B IB Franks Paul W PW Kritchevsky Stephen B SB Lehtimäki Terho T Loos Ruth J F RJ Orho-Melander Marju M Rotter Jerome I JI Wareham Nicholas J NJ Witteman Jacqueline C M JC Ferrucci Luigi L Dedoussis George G Cupples L Adrienne LA Nettleton Jennifer A JA

The American journal of clinical nutrition 20130501 6

<h4>Background</h4>Macronutrient intake varies substantially between individuals, and there is evidence that this variation is partly accounted for by genetic variants.<h4>Objective</h4>The objective of the study was to identify common genetic variants that are associated with macronutrient intake.<h4>Design</h4>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 question ...[more]

PMID: 23636237

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Project description:BackgroundThe epilepsies are a clinically heterogeneous group of neurological disorders. Despite strong evidence for heritability, genome-wide association studies have had little success in identification of risk loci associated with epilepsy, probably because of relatively small sample sizes and insufficient power. We aimed to identify risk loci through meta-analyses of genome-wide association studies for all epilepsy and the two largest clinical subtypes (genetic generalised epilepsy and focal epilepsy).MethodsWe combined genome-wide association data from 12 cohorts of individuals with epilepsy and controls from population-based datasets. Controls were ethnically matched with cases. We phenotyped individuals with epilepsy into categories of genetic generalised epilepsy, focal epilepsy, or unclassified epilepsy. After standardised filtering for quality control and imputation to account for different genotyping platforms across sites, investigators at each site conducted a linear mixed-model association analysis for each dataset. Combining summary statistics, we conducted fixed-effects meta-analyses of all epilepsy, focal epilepsy, and genetic generalised epilepsy. We set the genome-wide significance threshold at p<1·66 × 10(-8).FindingsWe included 8696 cases and 26 157 controls in our analysis. Meta-analysis of the all-epilepsy cohort identified loci at 2q24.3 (p=8·71 × 10(-10)), implicating SCN1A, and at 4p15.1 (p=5·44 × 10(-9)), harbouring PCDH7, which encodes a protocadherin molecule not previously implicated in epilepsy. For the cohort of genetic generalised epilepsy, we noted a single signal at 2p16.1 (p=9·99 × 10(-9)), implicating VRK2 or FANCL. No single nucleotide polymorphism achieved genome-wide significance for focal epilepsy.InterpretationThis meta-analysis describes a new locus not previously implicated in epilepsy and provides further evidence about the genetic architecture of these disorders, with the ultimate aim of assisting in disease classification and prognosis. The data suggest that specific loci can act pleiotropically raising risk for epilepsy broadly, or can have effects limited to a specific epilepsy subtype. Future genetic analyses might benefit from both lumping (ie, grouping of epilepsy types together) or splitting (ie, analysis of specific clinical subtypes).FundingInternational League Against Epilepsy and multiple governmental and philanthropic agencies.

Project description:Numerous studies have identified the various fat mass and obesity-associated (FTO) genetic variants associated with obesity and its metabolic consequences; however, the impact of dietary factors on these associations remains unclear. The aim of this study was to evaluate the association between FTO single nucleotide polymorphisms (SNPs), daily macronutrient intake, and obesity and its metabolic consequences. From 1549 Caucasian subjects of Polish origin, genotyped for the FTO SNPs (rs3751812, rs8044769, rs8050136, and rs9939609), 819 subjects were selected for gene-diet interaction analysis. Anthropometric measurements were performed and total body fat content and distribution, blood glucose and insulin concentration during oral glucose tolerance test (OGTT), and lipid profile were determined. Macronutrient intake was analyzed based on three-day food records, and daily physical activity levels were evaluated using the International Physical Activity Questionnaire Long Form (IPAQ-LF). Our study shows that carriers of the GG genotype of rs3751812 presented lower body weight, body mass index (BMI), total body fat content, and hip and waist circumference and presented lower obesity-related markers if more than 48% of daily energy intake was derived from carbohydrates and lower subcutaneous and visceral fat content when energy intake derived from dietary fat did not exceed 30%. Similar results were observed for rs8050136 CC genotype carriers. We did not notice any significant differences in obesity markers between genotypes of rs8044769, but we did observe a significant impact of diet-gene associations. Body weight and BMI were significantly higher in TT and CT genotype carriers if daily energy intake derived from carbohydrates was less than 48%. Moreover, in TT genotype carriers, we observed higher blood glucose concentration while fasting and during the OGTT test if more than 18% of total energy intake was derived from proteins. In conclusion, our results indicate that daily macronutrient intake may modulate the impact of FTO genetic SNPs on obesity and obesity-related metabolic consequences.

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

Project description:Background and objectivesConsumption of dietary fat has been reported to be associated with gastric cancer risk, but the results of epidemiologic studies remain inconsistent. We conducted a meta-analysis to summarize the evidence regarding the association between dietary fat intake and gastric cancer risk.MethodsA comprehensive search of PubMed and EMBASE was performed to identify observational studies providing quantitative estimates between dietary fat and gastric cancer risk. Random effects model was used to calculate the summary relative risk(SRR) in the highest versus lowest analysis. Categorical dose-response analysis was conducted to quantify the association between dietary fat intake and gastric cancer risk. Heterogeneity among studies was evaluated using I2 and tau2(between study variance)statistics. Subgroup analysis and publication bias analysis were also performed.ResultsTwenty-two articles were included in the meta-analysis. The SRR for gastric cancer was 1.18 for individuals with highest intake versus lowest intake of total fat (95% confidence interval [CI]: 0.999-1.39; n = 28; P< 0.001; tau2 = 0.12; I2 = 69.5%, 95% CI: 55%-79%) and 1.08 with a daily increase in total fat intake (20 g/d) (95%CI: 1.02-1.14; n = 6; P = 0.09; tau2 = 0.002; I2 = 46.8%, 95% CI: 0%-79%). Positive association between saturated fat intake (SRR = 1.31; 95%CI: 1.09-1.58;n = 18;P<0.001; tau2 = 0.08; I2 = 60.6%, 95% CI: 34%-76%), inverse association between polyunsaturated fat intake (SRR = 0.77; 95%CI: 0.65-0.92; n = 16; P = 0.003; tau2 = 0.06; I2 = 56.2%, 95% CI: 23%-75%) and vegetable fat intake (SRR = 0.55; 95%CI: 0.41-0.74; n = 4;P = 0.12; tau2 = 0.04; I2 = 48.6%, 95% CI: 0%-83%), and no association between monounsaturated fat intake (SRR = 1.00; 95%CI: 0.79-1.25; n = 14; P< 0.001; tau2 = 0.10; I2 = 63.0%, 95% CI: 34%-79%) and animal fat intake (SRR = 1.10; 95%CI: 0.90-1.33; n = 6; P = 0.13;tau2 = 0.02; I2 = 42.0%, 95% CI: 0%-70%) and gastric cancer risk were observed.ConclusionsOur results suggest that intake of total fat is potentially positively associated with gastric cancer risk, and specific subtypes of fats account for different effects. However, these findings should be confirmed by further well-designed cohort studies with detailed dietary assessments and strict control of confounders.

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Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake.

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Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake.

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