Dataset Information

Interactions between serum urate-associated genetic variants and sex on gout risk: analysis of the UK Biobank.

ABSTRACT: BACKGROUND:Sex-specific differences in the effect of genetic variants on serum urate levels have been described. The aim of this study was to systematically examine whether serum urate-associated genetic variants differ in their influence on gout risk in men and women. METHODS:This research was conducted using the UK Biobank Resource. Thirty single nucleotide polymorphisms (SNPs) associated with serum urate were tested for their association with gout in men and women of European ancestry, aged 40-69?years. Gene-sex interactions for gout risk were analysed using an interaction analysis in logistic regression models. RESULTS:Gout was present in 6768 (4.1%) men and 574 (0.3%) women, with an odds ratio (95% confidence interval) for men 13.42 (12.32-14.62) compared with women. In men, experiment-wide association with gout was observed for 21 of the 30 serum urate-associated SNPs tested, and in women for three of the 30 SNPs. Evidence for gene-sex interaction was observed for ABCG2 (rs2231142) and PDZK1 (rs1471633), with the interaction in ABCG2 driven by an amplified effect in men and in PDZK1 by an absence of effect in women. Similar findings were observed in a sensitivity analysis which excluded pre-menopausal women. For the other SNPs tested, no significant gene-sex interactions were observed. CONCLUSIONS:In a large population of European ancestry, ABCG2 and PDZK1 gene-sex interactions exist for gout risk, with the serum urate-raising alleles exerting a greater influence on gout risk in men than in women. In contrast, other serum urate-associated genetic variants do not demonstrate significant gene-sex interactions for gout risk.

SUBMITTER: Narang RK

PROVIDER: S-EPMC6327586 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundPrevious studies have noted significant variation in serum urate (sUA) levels, and it is unknown how this influences the accuracy of hyperuricemia classification based on single data points. Despite this known variability, hyperuricemic patients are often used as a control group in gout studies. Our objective was to determine the accuracy of hyperuricemia classifications based on single data points versus multiple data points given the degree of variability observed with serial measurements of sUA.MethodsData was analyzed from a cross-over clinical trial of urate-lowering therapy in young adults without a gout diagnosis. In the control phase, sUA levels used for this analysis were collected at 2-4 week intervals. Mean coefficient of variation for sUA was determined, as were rates of conversion between normouricemia (sUA ≤6.8 mg/dL) and hyperuricemia (sUA > 6.8 mg/dL).ResultsMean study participant (n = 85) age was 27.8 ± 7.0 years, with 39% female participants and 41% African-American participants. Mean sUA coefficient of variation was 8.5% ± 4.9% (1 to 23%). There was no significant difference in variation between men and women, or between participants initially normouricemic and those who were initially hyperuricemic. Among those initially normouricemic (n = 72), 21% converted to hyperuricemia during at least one subsequent measurement. The subgroup with initial sUA < 6.0 (n = 54) was much less likely to have future values in the range of hyperuricemia compared to the group with screening sUA values between 6.0-6.8 (n = 18) (7% vs 39%, p = 0.0037). Of the participants initially hyperuricemic (n = 13), 46% were later normouricemic during at least one measurement.ConclusionSingle sUA measurements were unreliable in hyperuricemia classification due to spontaneous variation. Knowing this, if a single measurement must be used in classification, it is worth noting that those with an sUA of < 6.0 mg/dL were less likely to demonstrate future hyperuricemic measurements and this could be considered a safer threshold to rule out intermittent hyperuricemia based on a single measurement point.Trial registrationData from parent study ClinicalTrials.gov Identifier: NCT02038179 .

Project description:Abstract Objectives A meta-analysis of 11 CHARGE cohorts (N = 63,599) suggested that genetic variants within or near the CHREBP locus may modify the associations between sugar sweetened beverage (SSB) consumption and high-density lipoprotein cholesterol (HDL-C) and triglyceride (TG) concentrations. The study objective was to replicate these findings in a large independent cohort. Methods Blood lipids and 24-hour recalls were available for 57,794 adults of European ancestry in the UK Biobank (2006-‘10). SSBs included “squash” and “fizzy” drinks derived from a single 24-hr recall. A total of 875 SNPs within or near the CHREBP locus were identified and included in this analysis. Associations between these SNPs and HDL-C and TG concentrations were quantified among participants who did not report SSB consumption (non-consumers, n = 45,866), reported ≥0.5 servings/day of SSB (consumers, n = 11,928), and a subset of consumers who reported ≥2 servings/day of SSB (high consumers, n = 3742). Interaction between SSB and selected SNPs on HDL-C and TG concentrations was evaluated by examining the difference in beta coefficients between strata. Results were considered statistically significant at a Bonferroni-corrected pinteract < 0.0001 (0.05/499 effective tests). Results A significant interaction between SSB consumption and TBL2-rs71556729 on HDL-C concentration previously observed in the meta-analysis was replicated in UK Biobank. However, we observed a stronger interaction for a SNP in high linkage disequilibrium (R2 = 0.93) FZD9-rs34821369 (MAF = 0.03, pinteract = 8.2E-05) with TBL2-rs71556729 (MAF = 0.03, pinteract = 0.0004). Among only SSB consumers, each additional minor G allele at FZD9-rs34821369 was associated with mean HDL-C concentrations 1.63 mg/dL (SE = 0.53, P = 0.002) higher than those with the major T allele. Conclusions Our results suggest that adults with the minor allele at FZD9-rs34821369 may be protected against SSB-induced low HDL-C concentrations. These results are consistent the findings from a prior meta-analysis of 11 cohorts. Funding Sources NIH, AHA, USDA-ARS. This research has been conducted using the UK Biobank Resource (Application Number 35,835).

Dataset Information

Interactions between serum urate-associated genetic variants and sex on gout risk: analysis of the UK Biobank.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets