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

Academic Article
Publication Date:
2015
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 × 10-8). Two top loci in interaction term analyses, RBFOX3 and ERO1LB-EDAR-ADD, 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 × 10-8), a region that has been associated with several obesity related traits, and TSPYL5 (men, Pdifflean-overweight = 9.1 × 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 (P difflean-obese= 2 × 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 obsogenic environment.
Iris type:
01.01 Articolo in rivista
Keywords:
breast cancer resistance protein; estradiol; glycan; urate; adipocyte; body mass; carbohydrate synthesis; controlled study; effect size; female; gene locus; genetic association; genetic risk; genetic variability; human; lean body weight; major clinical study; male; obesity; regression analysis; single nucleotide polymorphism; uric acid blood level
List of contributors:
Ciullo, Marina; Nutile, Teresa; Ruggiero, Daniela
Authors of the University:
CIULLO MARINA
NUTILE TERESA
RUGGIERO DANIELA
Handle:
https://iris.cnr.it/handle/20.500.14243/296469
Published in:
PLOS ONE
Journal
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http://www.scopus.com/record/display.url?eid=2-s2.0-84926688627&origin=inward
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