Dataset Information

Genome-wide scan identifies a quantitative trait locus at 4p15.3 for serum urate.

ABSTRACT: Elevated serum urate levels lead to gout and are associated with hypertension, metabolic syndrome, type 2 diabetes and cardiovascular diseases. The purpose of this study was to identify evidence for genetic linkage with serum urate and to determine whether variation within positional candidate genes is associated with serum urate levels in a non-European population. Genetic linkage analysis and single nucleotide polymorphism (SNP) genotyping was performed in a large family pedigree cohort from Mauritius. We assessed associations between serum urate levels and 97 SNPs in a positional candidate gene, SLC2A9. A genome-wide scan identified a new region with evidence for linkage for serum urate at 4p15.3. SNP genotyping identified significant association between six SNP variants in SLC2A9 and serum urate levels. Allelic and gender-based effects were noted for several SNPs. Significant correlations were also observed between serum urate levels and individual components of metabolic syndrome. Our study results implicate genetic variation in SLC2A9 in influencing levels of serum urate over a broad range of values in a large Mauritian family cohort.

SUBMITTER: Cummings N

PROVIDER: S-EPMC2987471 | biostudies-literature | 2010 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Genome-wide scan identifies a quantitative trait locus at 4p15.3 for serum urate.

Cummings Nik N Dyer Thomas D TD Kotea Navaratnam N Kowlessur Sudhir S Chitson Pierrot P Zimmet Paul P Blangero John J Jowett Jeremy B M JB

European journal of human genetics : EJHG 20100630 11

Elevated serum urate levels lead to gout and are associated with hypertension, metabolic syndrome, type 2 diabetes and cardiovascular diseases. The purpose of this study was to identify evidence for genetic linkage with serum urate and to determine whether variation within positional candidate genes is associated with serum urate levels in a non-European population. Genetic linkage analysis and single nucleotide polymorphism (SNP) genotyping was performed in a large family pedigree cohort from M ...[more]

PMID: 20588307

Similar Datasets

Project description:BACKGROUND:Heterosis has been suggested to be caused by dominance effects. We performed a joint genome-wide association analysis (GWAS) using data from multi-breed and crossbred beef cattle to identify single nucleotide polymorphisms (SNPs) with significant dominance effects associated with variation in growth and carcass traits and to understand the mode of action of these associations. METHODS:Illumina BovineSNP50 genotypes and phenotypes for 11 growth and carcass traits were available for 6796 multi-breed and crossbred beef cattle. After performing quality control, 42,610 SNPs and 6794 animals were used for further analyses. A single-SNP GWAS for the joint association of additive and dominance effects was conducted in purebred, crossbred, and combined datasets using the ASReml software. Genomic breed composition predicted from admixture analyses was included in the mixed effect model to account for possible population stratification and breed effects. A threshold of 10% genome-wide false discovery rate was applied to declare associations as significant. The significant SNPs with dominance association were mapped to their corresponding genes at 100 kb. RESULTS:Seven SNPs with significant dominance associations were detected for birth weight, weaning weight, pre-weaning daily gain, yearling weight and marbling score across the three datasets at a false discovery rate of 10%. These SNPs were located on bovine chromosomes 1, 3, 4, 6 and 21 and mapped to six putative candidate genes: U6atac, AGBL4, bta-mir-2888-1, REPIN1, ICA1 and NXPH1. These genes have interesting biological functions related to the regulation of gene expression, glucose and lipid metabolism and body fat mass. For most of the identified loci, we observed over-dominance association with the studied traits, such that the heterozygous individuals at any of these loci had greater genotypic values for the trait than either of the homozygous individuals. CONCLUSIONS:Our results revealed very few regions with significant dominance genetic effects across all the traits studied in the three datasets used. Regarding the SNPs that were detected with dominance associations, further investigation is needed to determine their relevance in crossbreeding programs assuming that dominance effects are the main cause of (or contribute usefully to) heterosis.

Project description:There is considerable evidence that human genetic variation influences gene expression. Genome-wide studies have revealed that mRNA levels are associated with genetic variation in or close to the gene coding for those mRNA transcripts - cis effects, and elsewhere in the genome - trans effects. The role of genetic variation in determining protein levels has not been systematically assessed. Using a genome-wide association approach we show that common genetic variation influences levels of clinically relevant proteins in human serum and plasma. We evaluated the role of 496,032 polymorphisms on levels of 42 proteins measured in 1200 fasting individuals from the population based InCHIANTI study. Proteins included insulin, several interleukins, adipokines, chemokines, and liver function markers that are implicated in many common diseases including metabolic, inflammatory, and infectious conditions. We identified eight Cis effects, including variants in or near the IL6R (p = 1.8x10(-57)), CCL4L1 (p = 3.9x10(-21)), IL18 (p = 6.8x10(-13)), LPA (p = 4.4x10(-10)), GGT1 (p = 1.5x10(-7)), SHBG (p = 3.1x10(-7)), CRP (p = 6.4x10(-6)) and IL1RN (p = 7.3x10(-6)) genes, all associated with their respective protein products with effect sizes ranging from 0.19 to 0.69 standard deviations per allele. Mechanisms implicated include altered rates of cleavage of bound to unbound soluble receptor (IL6R), altered secretion rates of different sized proteins (LPA), variation in gene copy number (CCL4L1) and altered transcription (GGT1). We identified one novel trans effect that was an association between ABO blood group and tumour necrosis factor alpha (TNF-alpha) levels (p = 6.8x10(-40)), but this finding was not present when TNF-alpha was measured using a different assay , or in a second study, suggesting an assay-specific association. Our results show that protein levels share some of the features of the genetics of gene expression. These include the presence of strong genetic effects in cis locations. The identification of protein quantitative trait loci (pQTLs) may be a powerful complementary method of improving our understanding of disease pathways.

Dataset Information

Genome-wide scan identifies a quantitative trait locus at 4p15.3 for serum urate.

Publications

Genome-wide scan identifies a quantitative trait locus at 4p15.3 for serum urate.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure