Dataset Information

Modulation of genetic associations with serum urate levels by body-mass-index in humans.

ABSTRACT: We tested for interactions between body mass index (BMI) and common genetic variants affecting serum urate levels, genome-wide, in up to 42569 participants. Both stratified genome-wide association (GWAS) analyses, in lean, overweight and obese individuals, and regression-type analyses in a non BMI-stratified overall sample were performed. The former did not uncover any novel locus with a major main effect, but supported modulation of effects for some known and potentially new urate loci. The latter highlighted a SNP at RBFOX3 reaching genome-wide significant level (effect size 0.014, 95% CI 0.008-0.02, Pinter= 2.6 x 10-8). Two top loci in interaction term analyses, RBFOX3 and ERO1LB-EDARADD, also displayed suggestive differences in main effect size between the lean and obese strata. All top ranking loci for urate effect differences between BMI categories were novel and most had small magnitude but opposite direction effects between strata. They include the locus RBMS1-TANK (men, Pdifflean-overweight= 4.7 x 10-8), a region that has been associated with several obesity related traits, and TSPYL5 (men, Pdifflean-overweight= 9.1 x 10-8), regulating adipocytes-produced estradiol. The top-ranking known urate loci was ABCG2, the strongest known gout risk locus, with an effect halved in obese compared to lean men (Pdifflean-obese= 2 x 10-4). Finally, pathway analysis suggested a role for N-glycan biosynthesis as a prominent urate-associated pathway in the lean stratum. These results illustrate a potentially powerful way to monitor changes occurring in obesogenic environment.

SUBMITTER: Huffman JE

PROVIDER: S-EPMC4374966 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Modulation of genetic associations with serum urate levels by body-mass-index in humans.

Huffman Jennifer E JE Albrecht Eva E Teumer Alexander A Mangino Massimo M Kapur Karen K Johnson Toby T Kutalik Zoltán Z Pirastu Nicola N Pistis Giorgio G Lopez Lorna M LM Haller Toomas T Salo Perttu P Goel Anuj A Li Man M Tanaka Toshiko T Dehghan Abbas A Ruggiero Daniela D Malerba Giovanni G Smith Albert V AV Nolte Ilja M IM Portas Laura L Phipps-Green Amanda A Boteva Lora L Navarro Pau P Johansson Asa A Hicks Andrew A AA Polasek Ozren O Esko Tõnu T Peden John F JF Harris Sarah E SE Murgia Federico F Wild Sarah H SH Tenesa Albert A Tin Adrienne A Mihailov Evelin E Grotevendt Anne A Gislason Gauti K GK Coresh Josef J D'Adamo Pio P Ulivi Sheila S Vollenweider Peter P Waeber Gerard G Campbell Susan S Kolcic Ivana I Fisher Krista K Viigimaa Margus M Metter Jeffrey E JE Masciullo Corrado C Trabetti Elisabetta E Bombieri Cristina C Sorice Rossella R Döring Angela A Reischl Eva E Strauch Konstantin K Hofman Albert A Uitterlinden Andre G AG Waldenberger Melanie M Wichmann H-Erich HE Davies Gail G Gow Alan J AJ Dalbeth Nicola N Stamp Lisa L Smit Johannes H JH Kirin Mirna M Nagaraja Ramaiah R Nauck Matthias M Schurmann Claudia C Budde Kathrin K Farrington Susan M SM Theodoratou Evropi E Jula Antti A Salomaa Veikko V Sala Cinzia C Hengstenberg Christian C Burnier Michel M Mägi Reedik R Klopp Norman N Kloiber Stefan S Schipf Sabine S Ripatti Samuli S Cabras Stefano S Soranzo Nicole N Homuth Georg G Nutile Teresa T Munroe Patricia B PB Hastie Nicholas N Campbell Harry H Rudan Igor I Cabrera Claudia C Haley Chris C Franco Oscar H OH Merriman Tony R TR Gudnason Vilmundur V Pirastu Mario M Penninx Brenda W BW Snieder Harold H Metspalu Andres A Ciullo Marina M Pramstaller Peter P PP van Duijn Cornelia M CM Ferrucci Luigi L Gambaro Giovanni G Deary Ian J IJ Dunlop Malcolm G MG Wilson James F JF Gasparini Paolo P Gyllensten Ulf U Spector Tim D TD Wright Alan F AF Hayward Caroline C Watkins Hugh H Perola Markus M Bochud Murielle M Kao W H Linda WH Caulfield Mark M Toniolo Daniela D Völzke Henry H Gieger Christian C Köttgen Anna A Vitart Veronique V

PloS one 20150326 3

We tested for interactions between body mass index (BMI) and common genetic variants affecting serum urate levels, genome-wide, in up to 42569 participants. Both stratified genome-wide association (GWAS) analyses, in lean, overweight and obese individuals, and regression-type analyses in a non BMI-stratified overall sample were performed. The former did not uncover any novel locus with a major main effect, but supported modulation of effects for some known and potentially new urate loci. The lat ...[more]

PMID: 25811787

Similar Datasets

Project description:Background/objectiveBody mass index (BMI) is a surrogate measure of adiposity but does not distinguish fat from lean or bone mass. The genetic determinants of BMI are thought to predominantly influence adiposity but this has not been confirmed. Here we characterise the association between BMI-related genetic variants and body composition in adults.Subjects/methodsAmong 9667 adults aged 29-64 years from the Fenland study, a genetic risk score for BMI (BMI-GRS) was calculated for each individual as the weighted sum of BMI-increasing alleles across 96 reported BMI-related variants. Associations between the BMI-GRS and body composition, estimated by dual-energy X-ray absorptiometry (DXA) scans, were examined using age-adjusted linear regression models, separately by sex.ResultsThe BMI-GRS was positively associated with all fat, lean and bone variables. Across body regions, associations of the greatest magnitude were observed for adiposity variables, for example, for each s.d. increase in BMI-GRS predicted BMI, we observed a 0.90 s.d. (95% confidence interval (CI): 0.71, 1.09) increase in total fat mass for men (P=3.75 × 10-21) and a 0.96 s.d. (95% CI: 0.77, 1.16) increase for women (P=6.12 × 10-22). Associations of intermediate magnitude were observed with lean variables, for example, total lean mass: men: 0.68 s.d. (95% CI: 0.49, 0.86; P=1.91 × 10-12); women: 0.85 s.d. (95% CI: 0.65, 1.04; P=2.66 × 10-17) and of a lower magnitude with bone variables, for example, total bone mass: men: 0.39 s.d. (95% CI: 0.20, 0.58; P=5.69 × 10-5); women: 0.45 s.d. (95% CI: 0.26, 0.65; P=3.96 × 106). Nominally significant associations with BMI were observed for 28 single-nucleotide polymorphisms. All 28 were positively associated with fat mass and 13 showed adipose-specific effects.ConclusionsIn adults, genetic susceptibility to elevated BMI influences adiposity more than lean or bone mass. This mirrors the association between BMI and body composition. The BMI-GRS can be used to model the effects of measured BMI and adiposity on health and other outcomes.

Project description:BackgroundApolipoprotein E (APOE) polymorphism is associated with lipid levels. Some studies have reported that blood lipid response to diet or obesity varies depending on APOE genotypes. The aim of this study was to assess the effect of APOE genotypes, the intake of saturated fatty acids (SFA), and obesity on serum lipid levels in Lithuanian adult population.Methodology/principal findingsA cross-sectional health survey was carried out in five municipalities of Lithuania. The random sample was obtained from lists of 25-64 year-old inhabitants registered at primary health care centres. The data from 996 subjects (416 men and 580 women) were analysed in this study. Two single-nucleotide polymorphisms (rs429358 and rs7412) were assessed using a real-time polymerase chain reaction. 24-hour recall and food frequency questionnaire were used for evaluation of dietary habits. Serum lipids were determined using enzymatic methods. Men and women with the APOE2 genotype had the lowest level of total cholesterol (TC) (p = 0.002 for men, and p = 0.02 for women) and low-density lipoprotein cholesterol (LDL-C) (p<0.001). Multivariate linear regression analysis showed that age, genotype APOE2, SFA intake, and body mass index (BMI) were significant determinants of TC and LDL-C level (with p values ranging from 0.043 to 0.001). Our data did not reveal any statistically significant interactions between APOE genotype and SFA intake or between APOE genotype and BMI regarding TC and LDL-C level (all p>0.05). However, the predictive power of the regression model for LDL-C improved when gene-BMI interaction and gene-BMI interaction plus gene-nutrient interaction were added (p = 0.04 and p = 0.032 for R(2) change, respectively).Conclusions/significanceAPOE genotypes, SFA intake, and obesity were found to be associated with blood lipid levels in Lithuanian adult population. Analysis of gene-diet and gene-obesity interactions did not confirm that the effects of diet and obesity on TC and LDL-C level significantly depended on APOE genotype.

Dataset Information

Modulation of genetic associations with serum urate levels by body-mass-index in humans.

Publications

Modulation of genetic associations with serum urate levels by body-mass-index in humans.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure