BackgroundFerritin positively associates with serum urate and an interventional study suggests that iron has a role in triggering gout flares. The objective of this study was to further explore the relationship between iron/ferritin and urate/gout.MethodsEuropean (100 cases, 60 controls) and Polynesian (100 cases, 60 controls) New Zealand (NZ) males and 189 US male cases and 60 male controls participated. The 10,727 participants without gout were from the Jackson Heart (JHS; African American = 1260) and NHANES III (European = 5112; African American = 4355) studies. Regression analyses were adjusted for age, sex, body mass index and C-reactive protein. To test for a causal relationship between ferritin and urate, bidirectional two-sample Mendelian randomization analysis was performed.ResultsSerum ferritin positively associated with gout in NZ Polynesian (OR (per 10 ng ml− 1 increase) = 1.03, p = 1.8E–03) and US (OR = 1.11, p = 7.4E–06) data sets but not in NZ European (OR = 1.00, p = 0.84) data sets. Ferritin positively associated with urate in NZ Polynesian (β (mg dl− 1) = 0.014, p = 2.5E–04), JHS (β = 0.009, p = 3.2E–05) and NHANES III (European β = 0.007, p = 5.1E–11; African American β = 0.011, p = 2.1E–16) data sets but not in NZ European (β = 0.009, p = 0.31) or US (β = 0.041, p = 0.15) gout data sets. Ferritin positively associated with the frequency of gout flares in two of the gout data sets. By Mendelian randomization analysis a one standard deviation unit increase in iron and ferritin was, respectively, associated with 0.11 (p = 8E–04) and 0.19 mg dl− 1 (p = 2E–04) increases in serum urate. There was no evidence for a causal effect of urate on iron/ferritin.ConclusionsThese data replicate the association of ferritin with serum urate. Increased ferritin levels associated with gout and flare frequency. There was evidence of a causal effect of iron and ferritin on urate.Electronic supplementary materialThe online version of this article (10.1186/s13075-018-1668-y) contains supplementary material, which is available to authorized users.

BackgroundIncreased coffee intake is associated with reduced serum urate concentrations and lower risk of gout. Specific alleles of the GCKR, ABCG2, MLXIPL, and CYP1A2 genes have been associated with both reduced coffee intake and increased serum urate in separate genome-wide association studies (GWAS). The aim of this study was to determine whether these single nucleotide polymorphisms (SNPs) influence the risk of gout through their effects on coffee consumption.MethodsThis research was conducted using the UK Biobank Resource. Data were available for 130,966 European participants aged 40–69 years. Gout status and coffee intake were tested for association with four urate-associated SNPs: GCKR (rs1260326), ABCG2 (rs2231142), MLXIPL (rs1178977), and CYP1A2 (rs2472297). Multiple regression and path analysis were used to examine whether coffee consumption mediated the effect of the SNPs on gout risk.ResultsCoffee consumption was inversely associated with gout (multivariate adjusted odds ratio (95% confidence interval (CI)) for any coffee consumption 0.75 (0.67–0.84, P = 9 × 10−7)). There was also evidence of a dose-effect with multivariate adjusted odds ratio (95% CI) per cup consumed per day of 0.85 (0.82–0.87, P = 9 × 10−32). The urate-increasing GCKR, ABCG2, MLXIPL, and CYP1A2 alleles were associated with reduced daily coffee consumption, with the strongest associations for CYP1A2 (beta −0.30, P = 8 × 10−40), and MLXIPL (beta −0.17, P = 3 × 10−8), and weaker associations for GCKR (beta −0.07, P = 3 × 10−10) and ABCG2 (beta −0.09, P = 2 × 10−9). The urate-increasing GCKR and ABCG2 alleles were associated with gout (multivariate adjusted p < 5 × 10−8 for both), but the urate-increasing MLXIPL and CYP1A2 alleles were not. In mediation analysis, the direct effects of GCKR and ABCG2 accounted for most of the total effect on gout risk, with much smaller indirect effects mediated by coffee consumption.ConclusionCoffee consumption is inversely associated with risk of gout. Although alleles at several SNPs associate with both lower coffee consumption and higher risk of gout, these SNPs largely influence gout risk directly, rather than indirectly through effects on coffee consumption.Electronic supplementary materialThe online version of this article (10.1186/s13075-018-1629-5) contains supplementary material, which is available to authorized users.

Background Gout is predicted by a number of comorbidities and lifestyle factors. We aimed to identify discrete phenotype clusters of these factors in a Swedish population-based health survey. In these clusters, we calculated and compared the incidence and relative risk of gout. Methods Cluster analyses were performed to group variables with close proximity and to obtain homogenous clusters of individuals (n = 22,057) in the Malmö Preventive Project (MPP) cohort. Variables clustered included obesity, kidney dysfunction, diabetes mellitus (DM), hypertension, cardiovascular disease (CVD), dyslipidemia, pulmonary dysfunction (PD), smoking, and the use of diuretics. Incidence rates and hazard ratios (HRs) for gout, adjusted for age and sex, were computed for each cluster. Results Five clusters (C1–C5) were identified. Cluster C1 (n = 16,063) was characterized by few comorbidities. All participants in C2 (n = 750) had kidney dysfunction (100%), and none had CVD. In C3 (n = 528), 100% had CVD and most participants were smokers (74%). C4 (n = 3673) had the greatest fractions of obesity (34%) and dyslipidemia (74%). In C5 (n = 1043), proportions with DM (51%), hypertension (54%), and diuretics (52%) were highest. C1 was by far the most common in the population (73%), followed by C4 (17%). These two pathways included 86% of incident gout cases. The four smaller clusters (C2–C5) had higher incidence rates and a 2- to 3-fold increased risk for incident gout. Conclusions Five distinct clusters based on gout-related comorbidities and lifestyle factors were identified. Most incident gout cases occurred in the cluster of few comorbidities, and the four comorbidity pathways had overall a modest influence on the incidence of gout.

Introduction The relationship between urate and biomarkers for Alzheimer's disease (AD) pathophysiology has not been investigated. Methods We examined whether serum concentration of urate was associated with cerebrospinal fluid biomarkers, amyloid beta (Aβ) 42 , Aβ 40 , phosphorylated tau (p‐tau), total tau (t‐tau), neurofilament light (NfL), and Aβ 42 /Aβ 40 ratio, in cognitively unimpaired 70‐year‐old individuals from Gothenburg, Sweden. We also evaluated whether possible associations were modulated by the apolipoprotein E ( APOE ) ε4 allele. Results Serum urate was positively associated with Aβ 42 in males (β = 0.55 pg/mL, P = .04). There was a positive urate– APOE ε4 interaction (1.24 pg/mL, P interaction = .02) in relation to Aβ 42 association. The positive urate and Aβ 42 association strengthened in male APOE ε4 carriers (β = 1.28 pg/mL, P = .01). Discussion The positive association between urate and Aβ 42 in cognitively healthy men may suggest a protective effect of urate against deposition of amyloid protein in the brain parenchyma, and in the longer term, maybe against AD dementia.