Genome-wide association analyses identify 18 new loci associated with serum urate concentrations

Clinical Predictors and Long-term Impact of Acute Kidney Injury on Progression of Diabetic Kidney Disease in Chinese Patients With Type 2 Diabetes

We aim to assess the long-term impact of acute kidney injury (AKI) on progression of diabetic kidney disease (DKD) and all-cause mortality and investigate determinants of AKI in Chinese patients with type 2 diabetes (T2D). A consecutive cohort of 9,096 Chinese patients with T2D from the Hong Kong Diabetes Register was followed for 12 years (mean ± SD age 57 ± 13.2 years; 46.9% men; median duration of diabetes 5 years). AKI was defined based on the Kidney Disease: Improving Global Outcomes (KDIGO) criteria using serum creatinine. Estimated glomerular filtration rate measurements were used to identify the first episode with chronic kidney disease (CKD) and end-stage renal disease (ESRD). Polygenic risk score (PRS) composed of 27 single nucleotide polymorphisms (SNPs) known to be associated with serum uric acid (SUA) in European populations was used to examine the role of SUA in pathogenesis of AKI, CKD, and ESRD. Validation was sought in an independent cohort including 6,007 patients (age 61.2 ± 10.9 years; 59.5% men; median duration of diabetes 10 years). Patients with AKI had a higher risk for developing incident CKD (hazard ratio 14.3 [95% CI 12.69-16.11]), for developing ESRD (12.1 [10.74-13.62]), and for all-cause death (7.99 [7.31-8.74]) compared with those without AKI. Incidence rate for ESRD among patients with no episodes of AKI and one, two, and three or more episodes of AKI was 7.1, 24.4, 32.4, and 37.3 per 1,000 person-years, respectively. Baseline SUA was a strong independent predictor for AKI. A PRS composed of 27 SUA-related SNPs was associated with AKI and CKD in both discovery and replication cohorts but not ESRD. Elevated SUA may increase the risk of DKD through increasing AKI. The identification of SUA as a modifiable risk factor and PRS as a nonmodifiable risk factor may facilitate the identification of individuals at high risk to prevent AKI and its long-term impact in T2D.

Excess comorbidities in gout: the causal paradigm and pleiotropic approaches to care

Gout is a common hyperuricaemic metabolic condition that leads to painful inflammatory arthritis and a high comorbidity burden, especially cardiometabolic-renal (CMR) conditions, including hypertension, myocardial infarction, stroke, obesity, hyperlipidaemia, type 2 diabetes mellitus and chronic kidney disease. Substantial advances have been made in our understanding of the excess CMR burden in gout, ranging from pathogenesis underlying excess CMR comorbidities, inferring causal relationships from Mendelian randomization studies, and potentially discovering urate crystals in coronary arteries using advanced imaging, to clinical trials and observational studies. Despite many studies finding an independent association between blood urate levels and risk of incident CMR events, Mendelian randomization studies have largely found that serum urate is not causal for CMR end points or intermediate risk factors or outcomes (such as kidney function, adiposity, metabolic syndrome, glycaemic traits or blood lipid concentrations). Although limited, randomized controlled trials to date in adults without gout support this conclusion. If imaging studies suggesting that monosodium urate crystals are deposited in coronary plaques in patients with gout are confirmed, it is possible that these crystals might have a role in the inflammatory pathogenesis of increased cardiovascular risk in patients with gout; removing monosodium urate crystals or blocking the inflammatory pathway could reduce this excess risk. Accordingly, data for CMR outcomes with these urate-lowering or anti-inflammatory therapies in patients with gout are needed. In the meantime, highly pleiotropic CMR and urate-lowering benefits of sodium-glucose cotransporter 2 (SGLT2) inhibitors and key lifestyle measures could play an important role in comorbidity care, in conjunction with effective gout care based on target serum urate concentrations according to the latest guidelines.

Promoter DNA Methylation in GWAS-Identified Genes as Potential Functional Elements for Blood Pressure: An Observational and Mendelian Randomization Study

Genome-wide association studies have identified numerous genetic loci for blood pressure (BP). However, the relationships of functional elements inside these loci with BP are not fully understood. This study represented an effort to determine if promoter DNA methylations inside BP-associated loci were associated with BP.We conducted a cross-sectional study investigating the association between promoter DNA methylations of 10 candidate genes and BP in 1,241 Chinese individuals. Twenty-one genomic fragments in the CpG Islands were sequenced. The associations of methylation levels with BP and hypertension were assessed in regression models. Mendelian randomization (MR) analysis was then applied to find supporting evidence for the identified associations.A total of 413 DNA methylation sites were examined in an observational study. Methylation levels of 24 sites in PRDM6, IGFBP3, SYT7, PDE3A, TBX2 and C17orf82 were significantly associated with BP. Methylation levels of PRDM6 and SYT7 were significantly associated with hypertension. Methylation levels of five sites (including cg06713098) in IGFBP3 were significantly associated with DBP. MR analysis found associations between the methylation levels of six CpG sites (cg06713098, cg14228300, cg23193639, cg21268650, cg10677697 and cg04812164) around the IGFBP3 promoter and DBP. Methylation levels of cg14228300 and cg04812164 were associated with SBP. By further applying several MR methods we showed that the associations may not be due to pleiotropy. Association between IGFBP3 mRNA levels in blood cells and BP was also found in MR analysis. This study identified promoter methylation as potential functional element for BP. The identified methylations may be involved in the regulatory pathway linking genetic variants to BP.

Association and interaction between dietary patterns and gene polymorphisms in Liangshan residents with hyperuricemia

Hyperuricemia (HUA) is associated with dietary and genetic factors. However, studies on dietary patterns and their interaction effect with genes on the risk of HUA are limited. We aimed to explore the association between dietary patterns and HUA, and dietary patterns—gene interactions on the risk of HUA. A population-based cross-sectional study was conducted in adults aged 18 and older in Liangshan Yi Autonomous Prefecture of China. Dietary consumption was collected using a standard Food Frequency Questionnaire. Vein blood samples were collected after overnight fasting, and DNA was extracted from peripheral blood leukocytes. Dietary patterns were derived using principal component and factor analysis. Of the 2646 participants, the prevalence of HUA was 26.8%. Three dietary patterns were classified. Of them, a dietary pattern with higher meat consumption (defined as meat-based) had the strongest association with HUA than a dietary pattern with plant-based or local special diet-based. A higher frequency of T allele at ABCG2 rs2231142 and SLC2A9 rs11722228 loci was observed in participants with HUA than those without HUA. An additive interaction of meat-based dietary pattern with rs2231142 locus was significantly associated with an increased risk of HUA. The relative excess risks of interaction, attributable proportion of interaction, and synergy index (S) were 0.482 (95% CI: 0.012–0.976), 0.203 (95% CI: 0.033–0.374), and 1.544 (95% CI: 1.012–2.355), respectively. In conclusion, a dietary pattern with meat-based was significantly associated with an increased risk of HUA. There was an additive interaction between a meat-based dietary pattern and the ABCG2 rs2231142 locus. Individuals with rs2231142 T allele were at higher risk of HUA than those with rs2231142 GG allele.

Genetic risk of hyperuricemia in hypertensive patients associated with antihypertensive drug therapy: a longitudinal study

Elevated serum uric acid (UA) level has been shown to be influenced by multiple genetic variants, but it remains uncertain how UA‐associated variants differ in their influence on hyperuricemia risk in people taking antihypertensive drugs. We examined a total of 43 UA‐related variants at 29 genes in 1840 patients with hypertension from a community‐based longitudinal cohort during a median 2.25‐year follow‐up (including 1031 participants with normal UA, 440 prevalent hyperuricemia at baseline, and 369 new‐onset hyperuricemia). Compared with the wild‐type genotypes, patients carrying the SLC2A9 rs3775948G allele or the rs13129697G allele had decreased risk of hyperuricemia, while patients carrying the SLC2A9 rs11722228T allele had increased risk of hyperuricemia, after adjustment for cardiovascular risk factors and correction for multiple comparisons; moreover, these associations were modified by the use of diuretics, β‐blockers, or angiotensin converting enzyme inhibitors. The rs10821905A allele of A1CF gene was associated with increased risk of hyperuricemia, and this risk was enhanced by diuretics use. The studied variants were not observed to confer risk for incident cardiovascular events during the follow‐up. In conclusion, the genes SLC2A9 and A1CF may serve as potential genetic markers for hyperuricemia risk in relation to antihypertensive drugs therapy in Chinese hypertensive patients.

DeepNull models non-linear covariate effects to improve phenotypic prediction and association power

Genome-wide association studies (GWASs) examine the association between genotype and phenotype while adjusting for a set of covariates. Although the covariates may have non-linear or interactive effects, due to the challenge of specifying the model, GWAS often neglect such terms. Here we introduce DeepNull, a method that identifies and adjusts for non-linear and interactive covariate effects using a deep neural network. In analyses of simulated and real data, we demonstrate that DeepNull maintains tight control of the type I error while increasing statistical power by up to 20% in the presence of non-linear and interactive effects. Moreover, in the absence of such effects, DeepNull incurs no loss of power. When applied to 10 phenotypes from the UK Biobank (n = 370K), DeepNull discovered more hits (+6%) and loci (+7%), on average, than conventional association analyses, many of which are biologically plausible or have previously been reported. Finally, DeepNull improves upon linear modeling for phenotypic prediction (+23% on average).

Genetic assessment of hyperuricemia and gout in Asian, Native Hawaiian, and Pacific Islander subgroups of pregnant women: biospecimens repository cross-sectional study

Background

Gout, an inflammatory condition, is characterized by the precipitation of monosodium urate crystals (MSU) in or around distal joints. The latter is caused by chronic hyperuricemia (HU)—high urate levels in the blood. Genetic variations in urate transporters play a significant role in determining urate levels within the human body, rendering some racial and ethnic groups more or less susceptible to developing either HU or gout. This study aims to estimate the frequencies of HU and gout risk alleles in Asian, Native Hawaiian, and Pacific Islander subgroups, using biorepository DNA samples.

Methods

The biospecimens repository at the University of Hawai’i provided DNA samples of consented post-partum women of Japanese, Filipino, Korean, Native Hawaiian, Samoan, and Marshallese descent. The DNA was previously extracted from maternal blood and genotyped at the Genomics and Bioinformatics Shared Resource, Cancer Center (Honolulu, HI). Nine urate genes: ABCG2, SLC2A9, SLC16A9, GCKR, SLC22A11, SLC22A12, LRR16A, PDZK1, and SLC17A1, were selected due to their significant association with HU and gout risk. Hardy–Weinberg Equilibrium (HWE) for genotype frequencies was assessed, using the Chi-Square test with p < 0.006 for statistical significance. Allele frequencies in our study were then compared to EUR from the 1000 Genomes Project Database Phase III, using Chi-square or Fisher's exact test, when appropriate. Bonferroni correction for multiple comparisons was used, with p < 0.006 for statistical significance.

Results

Our study involved 1059 post-partum women 18-year-old or older who self-reported their respective race and ethnicity, including Asian, Native Hawaiian, and Pacific Islander ancestry. The Asian subgroups included Japanese, Filipino, and Korean. The Pacific Islander subgroups included Marshallese and Samoan. None of the study participants had a history of gout. We excluded the PDZK1 gene from the final analysis due to its deviation from HWE (p < 0.006) across all the population subgroups, with eight loci remaining for cross-subgroup comparisons. Compared to EUR, the genetic polymorphism frequencies were significantly different-8/8 in Japanese, 6/8 in Korean, 6/8 in Filipino, 8/8 in Samoan, 6/8 in Native Hawaiian, and 6/8 in Marshallese. HU and gout risk alleles indices were 8, 6, 5, 5, 4, and 4 in Japanese, Filipino, Korean, Samoan, Marshallese, and Native Hawaiian, respectively. The percentage of cumulative risk alleles was 100% in both Japanese and Filipino, followed by 83.5% in Korean.

Conclusions

Compared to EUR, Asian subgroups, particularly Japanese, Filipino, and Korean, had the highest percentage of the cumulative uric acid risk alleles. These results could partly explain the increased risk of developing gout among some Asian ancestral subgroups compared to EUR.

Assessment of causal associations between uric acid and 25-hydroxyvitamin D levels

BACKGROUND

Previous observational studies have revealed the association between serum uric acid and 25-hydroxyvitamin D. However, the causality and the direction of the associations remain unknown. Thus, we performed a two-sample bidirectional Mendelian Randomization (MR) analysis to investigate the causal association between uric acid and 25-hydroxyvitamin D and to determine the direction of the association.

METHOD

Based on the summary-level GWAS data from large genome-wide association studies, several steps were taken in our analysis to select eligible single-nucleotide polymorphisms (SNPs), which were strongly related to exposure as the instrumental variables. We used different analytical methods, such as inverse-variance weighting (IVW) method, weighted median, MR-Egger regression, and weighted mode method, to make our result more robust and reliable. The IVW method was used as the primary analysis. The Cochran's Q test, MR-Egger intercept test, MR-PRESSO method, and "leave-one-out" sensitivity analysis was performed to evaluate the heterogeneities, horizontal pleiotropy, and robustness of the results. MR analyses were also conducted using genetic risk scores (GRS) as instrumental variables in both directions by using the same summary-level GWAS data.

RESULTS

Our two-sample MR analysis suggested a causal association of genetically predicted uric acid on 25-hydroxyvitamin D [IVW method: β(SE), -0.0352(0.0149); p = 0.0178], which suggested that a per mg/dl increase in uric acid was associated with a decrease of 0.74 nmol/L of 25-hydroxyvitamin D, and the above results remained stable in the sensitivity analysis. By contrast, four MR methods suggested no causal relationship of 25-hydroxyvitamin D on serum uric acid [IVW β(SE), 0.0139 (0.0635); p = 0.826; MR-Egger β(SE), 0.0671 (0.108); p = 0.537; weighted median β(SE), 0.0933 (0.0495); p = 0.0598; weighted mode β(SE), 0.0562 (0.0463); p = 0.228, respectively]. After excluding the SNPs, which were associated with confounding factors and outlier SNPs, the IVW method suggested that there was still no causal association of 25-hydroxyvitamin D on serum uric acid. The GRS approach showed similar results.

CONCLUSIONS

Serum uric acid may causally affect the 25-hydroxyvitamin D levels, whereas the causal role of 25-hydroxyvitamin D on uric acid was not supported in our MR analysis. Our findings suggest that increased levels of uric acid should prompt investigation for vitamin D deficiency.

EPIGENETIC FACTORS OF SERUM URIC ACID LEVEL AND RELATED GENE POLYMORPHISMS IN SHENYANG, CHINA

BACKGROUND

The purpose of this study was to explore the influencing factors of serum uric acid (SUA) level and related gene polymorphisms in the healthy population.

METHODS

A total of 346 healthy individuals screened from different areas in Shenyang City and 195 patients with high SUA levels were included.

RESULTS

The levels of TC (total cholesterol), HDL-C (high-density lipoprotein cholesterol), LDL-C (low-density lipoprotein cholesterol), TG (triglycerides), GLU (blood glucose) ALT (alanine aminotransferase), TBA (total bile acid), TBIL (total bilirubin), CR (creatinine) and CYSC (Cystatin C) were statistically different between the healthy and hyperuricemia population (P<0.05). However, there was no statistical difference in the UA level between the two groups (P>0.05). After adjusting for UA, TC, HDL-C, LDL-C, GLU, TBIL and CYSC, the additive and recessive models of rs2231142 were statistically significant in females (P<0.05). For males, haplotypes of A-C-A-A-G-G, A-C-G-C-G-G and A-T-G-A-A-G had significant difference between the healthy and hyperuricemia population (P<0.05). For females, the haplotypes of A-C-G-C-G-G and A-T-A-C-A-T had significant differences (P<0.05).

CONCLUSION

The distributions of SLC2A9 (solute carrier family 2 and facilitated glucose transporter member 9), ABCG2 (ATP-binding cassette G2), GCKR (glucokinase regulatory protein), KCNQ1, IGFIR (Insulin-like growth factor-I receptor) and VEGFR (Vascular Endothelial Growth Factor Receptor) were balanced in the population in Shenyang City. The haplotypes of A-C-A-A-G-G, A-C-G-C-G-G and A-T-G-A-A-G were the influencing factors of high SUA in the population in Shenyang City.

Associations between serum urate and telomere length and inflammation markers: Evidence from UK Biobank cohort

Objective

Hyperuricemia and gout have become gradually more common. The effect of serum urate on organism aging and systematic inflammation is not determined. This study aims to evaluate whether serum urate is causally associated with cellular aging markers and serum inflammation markers.

Methods

A Mendelian randomization study was performed on summary-level data from the largest published genome-wide association studies. Single nucleotide polymorphisms with a genome-wide significance level were selected as instrumental variables for leukocyte telomere length (LTL), and serum soluble makers of inflammation (CRP, IL-6, TNF-α, and IGF-1). Standard inverse variance weighted (IVW) method was used as the primary statistical method. The weighted median, MR-Egger regression, and MR-PRESSO methods were used for sensitivity analysis.

Results

An inverse causal association of genetically predicted serum urate levels and LTL was found using IVW method (OR: 0.96, 95%CI 0.95, 0.97; β=-0.040; SE=0.0072; P=4.37×10^-8). The association was also supported by MR results using MR-Egger method and weighted median method. The MR-PRESSO analysis and leave-one-out sensitivity analysis supported the robustness of the combined results. In terms of other aging-related serum biomarkers, there was no evidence supporting a causal effect of serum urate on CRP, IL-6, TNF-α, or IGF-1 levels.

Conclusions

Serum urate levels are negatively associated with telomere length but are not associated with serum soluble indicators of inflammation. Telomere length may be a critical marker that reflects urate-related organismal aging and may be a mechanism in the age-related pathologies and mortality caused by hyperuricemia.

The role of lipid traits in mediating the effect of body mass index on serum urate

OBJECTIVE

To explore whether total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and triglyceride (TG) are mediators in the pathway of body mass index (BMI) on serum urate and determine the proportion of the mediation effect.

METHODS

This study used observational and two-sample Mendelian randomization (MR) analyses to explore the mediation effects of TC, HDL, LDL, and TG in the pathway of BMI on serum urate. We determined the size and the extent to which these lipids mediate any effect of BMI on serum urate.

RESULTS

Observational analysis results showed that HDL and TG can partially explain the association of BMI on serum urate, and the proportion of mediation effect was 10.2% and 8.9%, respectively. MR results demonstrated that TG has a causal effect on serum urate (β = 0.22, 95% CI: 0.15, 0.29; p = 2.28×10^-10.) and its proportion of mediation effect was 14.1%. TC, HDL, and LDL are not the mediators in the pathway of BMI on serum urate in MR estimates.

CONCLUSION

To a certain extent, TG mediates the effect of BMI on serum urate, and the risk of gout may be reduced by controlling both BMI and TG.

Vitamin D pathway gene variation rs3740165 is associated with serological uric acid levels in healthy Chinese women

AIM

To investigate the relationship between gene polymorphisms involved in the vitamin D metabolic pathway and serum uric acid (UA) levels in Chinese women.

METHODS

Fifteen key genes within the vitamin D metabolic pathway were screened using 96 single nucleotide polymorphisms in a group of 1,206 (37.96 ± 13.08 years) unrelated healthy Chinese women (aged 20-85 years). Blood and urine tests were performed at the same time. The Wilcoxon Mann-Whitney test was used to compare groups aged ≤50 years and >50 years. The mean serum UA values were computed within each group of homozygous referent, heterozygous, and homozygous variant genotypes for each single nucleotide polymorphism.

RESULTS

The exclusion process left 1,169 participants (38.16 ± 13.13 years) for analysis. One single nucleotide polymorphism in the CUBN gene (rs3740165) was identified as being significantly associated with serum UA levels in the group aged over 50 years. The wild type (C/C) population had higher serum UA levels in this group (P<0.001). In women aged over 50 years, allele C was associated with a higher risk of hyperuricemia than allele T (odds ratio 2.752, 95% confidence interval 1.458-5.192; P = 0.002). There was also a higher risk of hyperuricemia in genotype TC + CC compared with genotype TT (odds ratio 3.326, 95% confidence interval 1.513-7.313; P = 0.003) in women over 50 years of age.

CONCLUSION

The results suggest that the CUBN gene contributes to variability in serum UA levels in healthy Chinese Han women over 50 years of age.

The role of obesity, type 2 diabetes, and metabolic factors in gout: A Mendelian randomization study

BACKGROUND

Several epidemiological studies have reported a possible correlation between risk of gout and metabolic disorders including type 2 diabetes, insulin resistance, obesity, dyslipidemia, and hypertension. However, it is unclear if this association is causal.

METHODS

We used Mendelian randomization (MR) to evaluate the causal relation between metabolic conditions and gout or serum urate concentration by inverse-variance-weighted (conventional) and weighted median methods. Furthermore, MR-Egger regression and MR-pleiotropy residual sum and outlier (PRESSO) method were used to explore pleiotropy. Genetic instruments for metabolic disorders and outcome (gout and serum urate) were obtained from several genome-wide association studies on individuals of mainly European ancestry.

RESULTS

Conventional MR analysis showed a robust causal association of increasing obesity measured by body mass index (BMI), high-density lipoprotein cholesterol (HDL), and systolic blood pressure (SBP) with risk of gout. A causal relationship between fasting insulin, BMI, HDL, triglycerides (TG), SBP, alanine aminotransferase (ALT), and serum urate was also observed. These results were consistent in weighted median method and MR-PRESSO after removing outliers identified. Our analysis also indicated that HDL and serum urate as well as gout have a bidirectional causal effect on each other.

CONCLUSIONS

Our study suggested causal effects between glycemic traits, obesity, dyslipidemia, blood pressure, liver function, and serum urate as well as gout, which implies that metabolic factors contribute to the development of gout via serum urate, as well as potential benefit of sound management of increased serum urate in patients with obesity, dyslipidemia, hypertension, and liver dysfunction.

Association Between Triglyceride-Glucose Index and Serum Uric Acid Levels: A Biochemical Study on Anthropometry in Non-Obese Type 2 Diabetes Mellitus Patients

PURPOSE

The triglyceride-glucose index (TyG) is positively correlated with serum uric acid (SUA) in patients with type 2 diabetes mellitus (T2DM). However, whether this relationship exists in non-obese T2DM patients remains unknown. The study investigated the relationship between TyG and SUA in Chinese non-obese T2DM patients and examined the prognostic value of TyG in hyperuricemia (HUA).

PATIENTS AND METHODS

In total, 719 T2DM patients who were not obese were enrolled from among those who visited the Hebei General Hospital. The patients were categorized into groups according to their SUA levels. The relationship between TyG and clinical parameters was examined through correlation analysis. To consider covariates and examine the independent impact of TyG on HUA, logistic regression was performed. The receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic value of TyG and homeostasis model assessment of insulin resistance (HOMA-IR) for HUA.

RESULTS

The HUA prevalence was 12.10%. TyG was statistically different among the four SUA groups, with lower TyG levels in the Q1, Q2, and Q3 groups than that in the Q4 group. TyG was positively correlated with SUA (r = 0.176, P < 0.001). Logistic regression exhibited that TyG and SUA were independently correlated (OR = 2.427, 95% CI = 1.134-5.195, P = 0.022) even after adjustment for confounding factors. The ROC curve showed that the predictive value of TyG for HUA was higher than that of HOMA-IR (AUROC = 0.613, P = 0.001).

CONCLUSION

TyG was positively correlated with SUA in non-obese T2DM patients. TyG may better predict HUA in non-obese T2DM patients than HOMA-IR.

Cut-Off Value of Serum Uric Acid for Development of Gout Disease in Patients with Multiple Co-Morbidities

Objective:

This study aimed to determine the association between hyperuricemia, comorbid diseases and risk of developing gout disease in a Turkish population in a long follow-up period.

Methods:

A total of 2000 Turkish adults were cross-sectionally analysed for serum urate levels in 2009 at the Pamukkale University Faculty of Medicine. All patients on regular follow-up at our tertiary health center (n=1322) were included in this study. Demographic features (age and gender), comorbid clinical conditions, and medication use were noted. The risk of developing gout and the determinant factors were investigated. Multivariate logistic regression analysis was performed to analyse causative effects of factors while receiver operating characteristic (ROC) curve analysis was used to identify optimal cut-off values of uric acid level for predicting the development of gout.

Results:

Among 1322 patients, the mean age was 56.9 (SD:14.68) years. 57.3% (n=758) of the patients were female. The most common co-morbid disease was chronic kidney disease (581, 43%), followed by hypertension (522, 39.4%). Gout developed in 25 patients (1.8%). Gout development risk and presence of all the above comorbidities were significantly higher in patients with serum urate ≥7mg/dl compared with <7mg/dl. Male gender and not using urate lowering drugs were the main risk factors for developing gout disease. ROC analysis of serum uric acid levels identified a cut-off value of >7 (AUC: 0.776, sensitivity 86.96%, specificity 66.74%).

Conclusion:

There is still a dilemma concerning the culprit effects of both comorbidities and hyperuricemia on the risk of developing gout disease.

OMICS in Chronic Kidney Disease: Focus on Prognosis and Prediction

Chronic kidney disease (CKD) patients are characterized by a high residual risk for cardiovascular (CV) events and CKD progression. This has prompted the implementation of new prognostic and predictive biomarkers with the aim of mitigating this risk. The ‘omics’ techniques, namely genomics, proteomics, metabolomics, and transcriptomics, are excellent candidates to provide a better understanding of pathophysiologic mechanisms of disease in CKD, to improve risk stratification of patients with respect to future cardiovascular events, and to identify CKD patients who are likely to respond to a treatment. Following such a strategy, a reliable risk of future events for a particular patient may be calculated and consequently the patient would also benefit from the best available treatment based on their risk profile. Moreover, a further step forward can be represented by the aggregation of multiple omics information by combining different techniques and/or different biological samples. This has already been shown to yield additional information by revealing with more accuracy the exact individual pathway of disease.

SLC22 Transporters in the Fly Renal System Regulate Response to Oxidative Stress In Vivo

Several SLC22 transporters in the human kidney and other tissues are thought to regulate endogenous small antioxidant molecules such as uric acid, ergothioneine, carnitine, and carnitine derivatives. These transporters include those from the organic anion transporter (OAT), OCTN/OCTN-related, and organic cation transporter (OCT) subgroups. In mammals, it has been difficult to show a clear in vivo role for these transporters during oxidative stress. Ubiquitous knockdowns of related Drosophila SLC22s-including transporters homologous to those previously identified by us in mammals such as the "Fly-Like Putative Transporters" FLIPT1 (SLC22A15) and FLIPT2 (SLC22A16)-have shown modest protection against oxidative stress. However, these fly transporters tend to be broadly expressed, and it is unclear if there is an organ in which their expression is critical. Using two tissue-selective knockdown strategies, we were able to demonstrate much greater and longer protection from oxidative stress compared to previous whole fly knockdowns as well as both parent and WT strains (CG6126: p < 0.001, CG4630: p < 0.01, CG16727: p < 0.0001 and CG6006: p < 0.01). Expression in the Malpighian tubule and likely other tissues as well (e.g., gut, fat body, nervous system) appear critical for managing oxidative stress. These four Drosophila SLC22 genes are similar to human SLC22 transporters (CG6126: SLC22A16, CG16727: SLC22A7, CG4630: SLC22A3, and CG6006: SLC22A1, SLC22A2, SLC22A3, SLC22A6, SLC22A7, SLC22A8, SLC22A11, SLC22A12 (URAT1), SLC22A13, SLC22A14)-many of which are highly expressed in the kidney. Consistent with the Remote Sensing and Signaling Theory, this indicates an important in vivo role in the oxidative stress response for multiple SLC22 transporters within the fly renal system, perhaps through interaction with SLC22 counterparts in non-renal tissues. We also note that many of the human relatives are well-known drug transporters. Our work not only indicates the importance of SLC22 transporters in the fly renal system but also sets the stage for in vivo studies by examining their role in mammalian oxidative stress and organ crosstalk.

Epigenome-wide association study of serum urate reveals insights into urate co-regulation and the SLC2A9 locus

Elevated serum urate levels, a complex trait and major risk factor for incident gout, are correlated with cardiometabolic traits via incompletely understood mechanisms. DNA methylation in whole blood captures genetic and environmental influences and is assessed in transethnic meta-analysis of epigenome-wide association studies (EWAS) of serum urate (discovery, n = 12,474, replication, n = 5522). The 100 replicated, epigenome-wide significant (p < 1.1E-7) CpGs explain 11.6% of the serum urate variance. At SLC2A9, the serum urate locus with the largest effect in genome-wide association studies (GWAS), five CpGs are associated with SLC2A9 gene expression. Four CpGs at SLC2A9 have significant causal effects on serum urate levels and/or gout, and two of these partly mediate the effects of urate-associated GWAS variants. In other genes, including SLC7A11 and PHGDH, 17 urate-associated CpGs are associated with conditions defining metabolic syndrome, suggesting that these CpGs may represent a blood DNA methylation signature of cardiometabolic risk factors. This study demonstrates that EWAS can provide new insights into GWAS loci and the correlation of serum urate with other complex traits.

Impact of adiposity on risk of female gout among those genetically predisposed: sex-specific prospective cohort study findings over >32 years

OBJECTIVES

To evaluate the joint (combined) association of excess adiposity and genetic predisposition with the risk of incident female gout, and compare to their male counterparts; and determine the proportion attributable to body mass index (BMI) only, genetic risk score (GRS) only, and to their interaction.

METHODS

We prospectively investigated potential gene-BMI interactions in 18 244 women from the Nurses' Health Study and compared with 10 888 men from the Health Professionals Follow-Up Study. GRS for hyperuricaemia was derived from 114 common urate-associated single nucleotide polymorphisms.

RESULTS

Multivariable relative risk (RR) for female gout was 1.49 (95% CI 1.42 to 1.56) per 5 kg/m² increment of BMI and 1.43 (1.35 to 1.52) per SD increment in the GRS. For their joint association of BMI and GRS, RR was 2.18 (2.03 to 2.36), more than the sum of each individual factor, indicating significant interaction on an additive scale (p for interaction <0.001). The attributable proportions of joint effect for female gout were 42% (37% to 46%) to adiposity, 37% (32% to 42%) to genetic predisposition and 22% (16% to 28%) to their interaction. Additive interaction among men was smaller although still significant (p interaction 0.002, p for heterogeneity 0.04 between women and men), and attributable proportion of joint effect was 14% (6% to 22%).

CONCLUSIONS

While excess adiposity and genetic predisposition both are strongly associated with a higher risk of gout, the excess risk of both combined was higher than the sum of each, particularly among women.

Causal Inference of Carnitine on Blood Pressure and potential mediation by uric acid: A mendelian randomization analysis

Background

Dietary change alters blood pressure (BP) but the specific causal dietary elements are unclear. Given previous observational data suggesting serum carnitine or uric acid affect BP, we investigated the role of serum carnitine and serum uric acid concentrations on BP, and considered mediation by lipids and insulin resistance using two-sample bi-directional Mendelian randomization (MR) analysis.

Methods

We performed MR to characterize bi-directional causal relationships of carnitine or uric acid on cardiometabolic traits. We performed two-sample MR using genome-wide association summary data from separate large-scale genomic analyses of carnitine, uric acid, BP, lipids, and glycemic traits. We used inverse variance weighted (IVW) meta-analysis and MR Egger regression to test for causal relations in the absence and presence of pleiotropy, respectively, and performed sensitivity analyses to identify confounders and intermediates.

Results

In our analysis, carnitine was directly, causally associated with systolic BP (IVW effect = 0.2, causal p-value = 0.03) but not diastolic BP (IVW causal p = 0.1). Our findings additionally support direct and indirect relationships of carnitine on TG and on uric acid. No causal associations of carnitine were found with glycemic traits. Uric acid was not associated with BP, nor TG.

Conclusion

Two-sample bi-directional MR demonstrated an unconfounded causal effect of carnitine, but not uric acid, on systolic but not diastolic BP, suggesting a role of carnitine in arterial stiffness. Carnitine, but not uric acid, also has direct and indirect effects on TG but are independent of the causal effect of carnitine on systolic BP.

Alu insertion variants alter gene transcript levels

Alu are high copy number interspersed repeats that have accumulated near genes during primate and human evolution. They are a pervasive source of structural variation in modern humans. Impacts that Alu insertions may have on gene expression are not well understood, although some have been associated with expression quantitative trait loci (eQTLs). Here, we directly test regulatory effects of polymorphic Alu insertions in isolation of other variants on the same haplotype. To screen insertion variants for those with such effects, we used ectopic luciferase reporter assays and evaluated 110 Alu insertion variants, including more than 40 with a potential role in disease risk. We observed a continuum of effects with significant outliers that up- or down-regulate luciferase activity. Using a series of reporter constructs, which included genomic context surrounding the Alu, we can distinguish between instances in which the Alu disrupts another regulator and those in which the Alu introduces new regulatory sequence. We next focused on three polymorphic Alu loci associated with breast cancer that display significant effects in the reporter assay. We used CRISPR to modify the endogenous sequences, establishing cell lines varying in the Alu genotype. Our findings indicate that Alu genotype can alter expression of genes implicated in cancer risk, including PTHLH, RANBP9, and MYC These data show that commonly occurring polymorphic Alu elements can alter transcript levels and potentially contribute to disease risk.

Urate transport in health and disease

Circulation of urate levels is determined by the balance between urate production and excretion, homeostasis regulated by the function of urate transporters in key epithelial tissues and cell types. Our understanding of these physiological processes and identification of the genes encoding the urate transporters has advanced significantly, leading to a greater ability to predict risk for urate-associated diseases and identify new therapeutics that directly target urate transport. Here, we review the identified urate transporters and their organization and function in the renal tubule, the intestinal enterocytes, and other important cell types to provide a fuller understanding of the complicated process of urate homeostasis and its role in human diseases. Furthermore, we review the genetic tools that provide an unbiased catalyst for transporter identification as well as discuss the role of transporters in determining the observed significant gender differences in urate-associated disease risk.

Genetic Correlation Analysis and Transcriptome-wide Association Study Suggest the Overlapped Genetic Mechanism between Gout and Attention-deficit Hyperactivity Disorder

OBJECTIVES

Gout is a common inflammatory arthritis, which is caused by hyperuricemia. Limited efforts have been paid to systematically explore the relationships between gout and common psychiatric disorders.

METHODS

Genome-wide association study summary data of gout were obtained from the GeneATLAS, which contained 452,264 participants including 3,528 gout cases. Linkage disequilibrium score regression (LDSC) was first conducted to evaluate the genetic relationships between gout and 5 common psychiatric disorders. Transcriptome-wide association studies (TWAS) was then conducted to explore the potential biological mechanism underlying the observed genetic correlation between gout and attention-deficit hyperactivity disorder (ADHD). The Database for Annotation, Visualization and Integrated Discovery online functional annotation system was applied for pathway enrichment analysis and gene ontology enrichment analysis.

RESULTS

LDSC analysis observed significant genetic correlation between gout and ADHD (genetic correlation coefficients = 0.29, standard error = 0.09 and P value = 0.0015). Further TWAS of gout identified 105 genes with P value < 0.05 in muscle skeleton and 228 genes with P value < 0.05 in blood. TWAS of ADHD also detected 300 genes with P value < 0.05 in blood. Further comparing the TWAS results identified 9 common candidate genes shared by gout and ADHD, such as CD300C (P_gout = 0.0040; P_ADHD = 0.0226), KDM6B (P_gout = 0.0074; P_ADHD = 0.0460), and BST1 (P_gout = 0.0349; P_ADHD = 0.03560).

CONCLUSION

We observed genetic correlation between gout and ADHD and identified multiple candidate genes for gout and ADHD.

Identifying causality, genetic correlation, priority and pathways of large-scale complex exposures of breast and ovarian cancers

BACKGROUND

Genetic correlations, causalities and pathways between large-scale complex exposures and ovarian and breast cancers need systematic exploration.

METHODS

Mendelian randomisation (MR) and genetic correlation (GC) were used to identify causal biomarkers from 95 cancer-related exposures for risk of breast cancer [BC: oestrogen receptor-positive (ER + BC) and oestrogen receptor-negative (ER - BC) subtypes] and ovarian cancer [OC: high-grade serous (HGSOC), low-grade serous, invasive mucinous (IMOC), endometrioid (EOC) and clear cell (CCOC) subtypes].

RESULTS

Of 31 identified robust risk factors, 16 were new causal biomarkers for BC and OC. Body mass index (BMI), body fat mass (BFM), comparative body size at age 10 (CBS-10), waist circumference (WC) and education attainment were shared risk factors for overall BC and OC. Childhood obesity, BMI, CBS-10, WC, schizophrenia and age at menopause were significantly associated with ER + BC and ER - BC. Omega-6:omega-3 fatty acids, body fat-free mass and basal metabolic rate were positively associated with CCOC and EOC; BFM, linoleic acid, omega-6 fatty acids, CBS-10 and birth weight were significantly associated with IMOC; and body fat percentage, BFM and adiponectin were significantly associated with HGSOC. Both GC and MR identified 13 shared factors. Factors were stratified into five priority levels, and visual causal networks were constructed for future interventions.

CONCLUSIONS

With analysis of large-scale exposures for breast and ovarian cancers, causalities, genetic correlations, shared or specific factors, risk factor priority and causal pathways and networks were identified.

Interaction of Alcohol Consumption and ABCG2 rs2231142 Variant Contributes to Hyperuricemia in a Taiwanese Population

Background: ABCG2 rs2231142 is an important genetic factor that contributes to the development of gout and hyperuricemia (HUA). Epidemiologic studies have demonstrated that lifestyle risk factors of HUA (e.g., alcohol consumption) and genetic predisposition (e.g., ABCG2 gene) together, contribute to enhanced serum uric acid levels. However, the interaction between ABCG2 rs2231142, alcohol consumption, and HUA in the Taiwanese population is still unclear. Therefore, this study investigated whether the risk of HUA is associated with ABCG2 rs2231142 variants and how this is affected by alcohol consumption. Method: study subjects were selected from the participants of the Taiwan Biobank database. Overall, 114,540 participants aged 30 to 70 years were enrolled in this study. The interaction between ABCG2 rs2231142, alcohol consumption, and serum uric acid (sUA) levels was analyzed by multiple logistic regression models. Results: the prevalence of HUA was 32.7% and 4.4 % in the male and female populations, respectively. In the whole study population, the minor T allele of ABCG2 rs2231142 was significantly associated with HUA risk, and the occurrence of HUA was high in TT genotype and TG genotype. The risk of HUA was significantly increased by the combined association of ABCG2 rs2231142 and alcohol consumption for TG/TT genotype compared to the GG genotype (wild-type genotype), especially among women. Conclusion: the ABCG2 rs2231142 is a crucial genetic locus for sUA levels in the Taiwanese population and our findings revealed that alcohol consumption combined with the ABCG2 rs2231142 risk allele contributes to increased HUA risk.

The genetic basis of urate control and gout: Insights into molecular pathogenesis from follow-up study of genome-wide association study loci

This review focuses on the post-genome-wide association study (GWAS) era in gout, i.e., the translation of GWAS genetic association signals into biologically informative knowledge. Analytical and experimental follow-up of individual loci, based on the identification of causal genetic variants, reveals molecular pathogenic pathways. We summarize in detail the largest GWAS in urate to date, then we review follow-up studies and molecular insights from ABCG2, HNF4A, PDZK1, MAF, GCKR, ALDH2, ALDH16A1, SLC22A12, SLC2A9, ABCC4, and SLC22A13, including the role of insulin signaling. One common factor in these pathways is the importance of transcriptional control, including the HNF4α transcription factor. The new molecular knowledge reveals new targets for intervention to manage urate levels and prevent gout.

SNP rs4971059 predisposes to breast carcinogenesis and chemoresistance via TRIM46-mediated HDAC1 degradation

Identification of the driving force behind malignant transformation holds the promise to combat the relapse and therapeutic resistance of cancer. We report here that the single nucleotide polymorphism (SNP) rs4971059, one of 65 new breast cancer risk loci identified in a recent genome-wide association study (GWAS), functions as an active enhancer of TRIM46 expression. Recreating the G-to-A polymorphic switch caused by the SNP via CRISPR/Cas9-mediated homologous recombination leads to an overt upregulation of TRIM46. We find that TRIM46 is a ubiquitin ligase that targets histone deacetylase HDAC1 for ubiquitination and degradation and that the TRIM46-HDAC1 axis regulates a panel of genes, including ones critically involved in DNA replication and repair. Consequently, TRIM46 promotes breast cancer cell proliferation and chemoresistance in vitro and accelerates tumor growth in vivo. Moreover, TRIM46 is frequently overexpressed in breast carcinomas, and its expression is correlated with lower HDAC1 expression, higher histological grades, and worse prognosis of the patients. Together, our study links SNP rs4971059 to replication and to breast carcinogenesis and chemoresistance and support the pursuit of TRIM46 as a potential target for breast cancer intervention.

Uric acid extrarenal excretion: the gut microbiome as an evident yet understated factor in gout development

Humans do not produce uricase, an enzyme responsible for degrading uric acid. However, some bacteria residing in the gut can degrade one-third of the dietary and endogenous uric acid generated daily. New insights based on metagenomic and metabolomic approaches provide a new interest in exploring the involvement of gut microbiota in gout. Nevertheless, the exact mechanisms underlying this association are complex and have not been widely discussed. In this study, we aimed to review the evidence that suggests uric acid extrarenal excretion and gut microbiome are potential risk factors for developing gout. A literature search was performed in PubMed, Web of Science, and Google Scholar using several keywords, including "gut microbiome AND gout". A remarkable intestinal dysbiosis and shifts in abundance of certain bacterial taxa in gout patients have been consistently reported among different studies. Under this condition, bacteria might have developed adaptive mechanisms for de novo biosynthesis and salvage of purines, and thus, a concomitant alteration in uric acid metabolism. Moreover, gut microbiota can produce substrates that might cross the portal vein so the liver can generate de novo purinogenic amino acids, as well as uric acid. Therefore, the extrarenal excretion of uric acid needs to be considered as a factor in gout development. Nevertheless, further studies are needed to fully understand the role of gut microbiome in uric acid production and its extrarenal excretion, and to point out possible bacteria or bacterial enzymes that could be used as probiotic coadjutant treatment in gout patients.

mGWAS identification of six novel single nucleotide polymorphism loci with strong correlation to gastric cancer

BACKGROUND

Metabolite genome-wide association studies (mGWAS) are key for understanding the genetic regulation of metabolites in complex diseases including cancers. Although mGWAS has revealed hundreds of metabolomics quantitative trait loci (mQTLs) in the general population, data relating to gastric cancer (GC) are still incomplete.

METHODS

We identified mQTLs associated with GC by analyzing genome-wide and metabolome-wide datasets generated from 233 GC patients and 233 healthy controls.

RESULTS

Twenty-two metabolites were statistically different between GC cases and healthy controls, and all of them were associated with the risk of gastric cancer. mGWAS analyses further revealed that 9 single nucleotide polymorphisms (SNPs) were significantly associated with 3 metabolites. Of these 9 SNPs, 6 loci were never reported in the previous mGWAS studies. Surprisingly, 4 of 9 SNPs were significantly enriched in genes involved in the T cell receptor signaling pathway.

CONCLUSIONS

Our study unveiled several novel GC metabolite and genetic biomarkers, which may be implicated in the prevention and diagnosis of gastric cancer.

Protein-coding repeat polymorphisms strongly shape diverse human phenotypes

Many human proteins contain domains that vary in size or copy number because of variable numbers of tandem repeats (VNTRs) in protein-coding exons. However, the relationships of VNTRs to most phenotypes are unknown because of difficulties in measuring such repetitive elements. We developed methods to estimate VNTR lengths from whole-exome sequencing data and impute VNTR alleles into single-nucleotide polymorphism haplotypes. Analyzing 118 protein-altering VNTRs in 415,280 UK Biobank participants for association with 786 phenotypes identified some of the strongest associations of common variants with human phenotypes, including height, hair morphology, and biomarkers of health. Accounting for large-effect VNTRs further enabled fine-mapping of associations to many more protein-coding mutations in the same genes. These results point to cryptic effects of highly polymorphic common structural variants that have eluded molecular analyses to date.

Association of ABCG2 rs2231142 Allele and BMI With Hyperuricemia in an East Asian Population

Objectives: Genetic variants and obesity are risk factors for hyperuricemia (HUA). Recent genome-wide association studies have identified ABCG2 rs2231142 as one of the most prominent genetic variants for HUA in an East Asian population. Nevertheless, no large-scale studies have demonstrated any interactive effects between this variant and obesity on serum urate level in Asians. This study aimed to determine the interaction of ABCG2 rs2231142 variant and body mass index (BMI) and its effect on risk of HUA in an East Asian population.

Methods: The study was conducted using the Taiwan Biobank database, a population-based biomedical research database of patients with Taiwanese Han Chinese ancestry aged 30–70years between September 2014 and May 2017. Detailed physical information on participants were collected by questionnaires and genotyping using Affymetrix TWB 650K SNP chip. The primary outcome was HUA, defined as a serum uric acid level>7.0mg/dl. Odds ratio (OR) of HUA was analyzed using logistic regression models and the effects of interaction between ABCG2 rs2231142 variants and BMI on serum uric acid level were explored.

Results: We identified 25,245 subjects, 4,228 (16.75%) of whom had HUA. The prevalence of HUA was 30% in men and 3.8% in women. The risk of HUA was significantly associated with ABCG2 rs2231142 risk T allele, with more HUA in TT genotype (OR: 2.40, 95% CI: 2.11–2.72, p<0.001) and TG genotype (OR: 1.64, 95% CI: 1.51–1.78, p<0.001) in men, and TT genotype (OR: 2.42, 95% CI: 1.83–3.20, p<0.001) and TG genotype (OR: 1.82, 95% CI: 1.46–2.23, p<0.001) in women, compared with their counterparts. Moreover, we found a strong genetic-environmental interaction associated with the risk of HUA. There was increased risk of HUA by the interaction of ABCG2 rs2231142 variant and BMI for TT genotype (OR: 7.42, 95% CI: 2.54–21.7, p<0.001) and TG genotype (OR: 4.25, 95% CI: 2.13–8.47, p<0.001) in men compared with the GG genotype in men, and for TT genotype (OR: 25.43, 95% CI: 3.75–172.41, p<0.001) and TG genotype (OR: 3.05, 95% CI: 0.79–11.71, p=0.011) in women compared with the GG genotype in women.

Conclusion: The risk of HUA was markedly increased by the interaction of ABCG2 rs2231142 variant and BMI, both in men and in women. Body weight control and reduction in BMI are recommended in high-risk patients with the ABCG2 rs2231142 risk T allele.

Using multiple Mendelian randomization approaches and genetic correlations to understand obesity, urate, and gout

Observational studies suggest relationships between obesity, urate, and gout but are possibly confounded. We assessed whether genetically determined obesity, higher urate (and related traits), and gout were causal using multiple Mendelian randomization (MR) approaches and linkage disequilibrium score regression for genetic correlations (rg). For data, we used genome-wide association study summary statistics available through MR-Base. We observed that obesity increased urate (beta = 0.127; 95% CI = 0.098, 0.157; P-value = 1.2E-17; rg = 0.25 [P-value = 0.001]) and triglycerides (beta = 0.082; 95% CI = 0.065, 0.099; P-value = 1.2E-21; rg = 0.23 [P-value = 8.8E-12]) and decreased high-density lipoprotein cholesterol (HDL) (beta = - 0.083; 95% CI = - 0.101, - 0.065; P-value = 2.5E-19; rg = - 0.28; [P-value = 5.2E-24]). Higher triglycerides increased urate (beta = 0.198; 95% CI = 0.146, 0.251; P-value = 8.9E-14; rg = 0.29 [P-value = 0.001]) and higher HDL decreased urate (beta = - 0.109; 95% CI = - 0.148, - 0.071; P-value = 2.7E- 08; rg = - 0.21 [P-value = 9.8E-05]). Higher urate (OR = 1.030; 95% CI = 1.028, 1.032; P-value = 1.1E-130; rg = 0.89 [P-value = 1.7E-55]) and obesity caused gout (OR = 1.003; 95% CI = 1.001, 1.004; P-value = 1.3E-04; rg = 0.23 [P-value = 2.7E-05]). Obesity on gout with urate as a mediator revealed all the effect of obesity on gout occurred through urate. Obesity on low-density lipoprotein cholesterol (LDL) was null (beta = -0.011; 95% CI = -0.030, 0.008; P-value = 2.6E-01; rg = 0.03 [P-value = 0.369]). A multivariable MR of obesity, HDL, and triglycerides on urate showed obesity influenced urate when accounting for HDL and triglycerides. Obesity's impact on urate was exacerbated by it decreasing HDL.

Characterization of a Compound Heterozygous SLC2A9 Mutation That Causes Hypouricemia

Renal hypouricemia is a rare genetic disorder. Hypouricemia can present as renal stones or exercise-induced acute renal failure, but most cases are asymptomatic. Our previous study showed that two recessive variants of SLC22A12 (p.Trp258*, pArg90His) were identified in 90% of the hypouricemia patients from two independent cohorts: the Korean genome and epidemiology study (KoGES) and the Korean Cancer Prevention Study (KCPS-II). In this work, we investigate the genetic causes of hypouricemia in the rest of the 10% of unsolved cases. We found a novel non-synonymous mutation of SLC2A9 (voltage-sensitive uric acid transporter) in the whole-exome sequencing (WES) results. Molecular dynamics prediction suggests that the novel mutation p.Met126Val in SLCA9b (p.Met155Val in SLC2A9a) hinders uric acid transport through a defect of the outward open geometry. Molecular analysis using Xenopus oocytes confirmed that the p.Met126Val mutation significantly reduced uric acid transport but does not affect the SLC2A9 protein expression level. Our results will shed light on a better understanding of SLC2A9-mediated uric acid transport and the development of a uric acid-lowering agent.

Quantile-Dependent Expressivity of Serum Uric Acid Concentrations

OBJECTIVE

"Quantile-dependent expressivity" occurs when the effect size of a genetic variant depends upon whether the phenotype (e.g., serum uric acid) is high or low relative to its distribution. Analyses were performed to test whether serum uric acid heritability is quantile-specific and whether this could explain some reported gene-environment interactions.

METHODS

Serum uric acid concentrations were analyzed from 2151 sibships and 12,068 offspring-parent pairs from the Framingham Heart Study. Quantile-specific heritability from offspring-parent regression slopes (β OP, h 2 = 2β OP/(1 + r spouse)) and full-sib regression slopes (β FS, h 2 = {(1 + 8r spouse β FS)0.5 - 1}/(2r spouse)) was robustly estimated by quantile regression with nonparametric significance assigned from 1000 bootstrap samples.

RESULTS

Quantile-specific h 2 (±SE) increased with increasing percentiles of the offspring's sex- and age-adjusted uric acid distribution when estimated from β OP (P trend = 0.001): 0.34 ± 0.03 at the 10th, 0.36 ± 0.03 at the 25th, 0.41 ± 0.03 at the 50th, 0.46 ± 0.04 at the 75th, and 0.49 ± 0.05 at the 90th percentile and when estimated from β FS (P trend = 0.006). This is consistent with the larger genetic effect size of (1) the SLC2A9 rs11722228 polymorphism in gout patients vs. controls, (2) the ABCG2 rs2231142 polymorphism in men vs. women, (3) the SLC2A9 rs13113918 polymorphism in obese patients prior to bariatric surgery vs. two-year postsurgery following 29 kg weight loss, (4) the ABCG2 rs6855911 polymorphism in obese vs. nonobese women, and (5) the LRP2 rs2544390 polymorphism in heavier drinkers vs. abstainers. Quantile-dependent expressivity may also explain the larger genetic effect size of an SLC2A9/PKD2/ABCG2 haplotype for high vs. low intakes of alcohol, chicken, or processed meats.

CONCLUSIONS

Heritability of serum uric acid concentrations is quantile-specific.

Sex differences in genetic architecture in the UK Biobank

Males and females present differences in complex traits and in the risk of a wide array of diseases. Genotype by sex (GxS) interactions are thought to account for some of these differences. However, the extent and basis of GxS are poorly understood. In the present study, we provide insights into both the scope and the mechanism of GxS across the genome of about 450,000 individuals of European ancestry and 530 complex traits in the UK Biobank. We found small yet widespread differences in genetic architecture across traits. We also found that, in some cases, sex-agnostic analyses may be missing trait-associated loci and looked into possible improvements in the prediction of high-level phenotypes. Finally, we studied the potential functional role of the differences observed through sex-biased gene expression and gene-level analyses. Our results suggest the need to consider sex-aware analyses for future studies to shed light onto possible sex-specific molecular mechanisms.

Variants in urate transporters, ADH1B, GCKR and MEPE genes associate with transition from asymptomatic hyperuricaemia to gout: results of the first gout versus asymptomatic hyperuricaemia GWAS in Caucasians using data from the UK Biobank

OBJECTIVES

To perform a genome-wide association study (GWAS) of gout cases versus asymptomatic hyperuricaemia (AH) controls, and gout cases versus normouricaemia controls, and to generate a polygenic risk score (PRS) to determine gout-case versus AH-control status.

METHODS

Gout cases and AH controls (serum urate (SU) ≥6.0 mg/dL) from the UK Biobank were divided into discovery (4934 cases, 56 948 controls) and replication (2115 cases, 24 406 controls) cohorts. GWAS was conducted and PRS generated using summary statistics in discovery cohort as the base dataset and the replication cohort as the target dataset. The predictive ability of the model was evaluated. GWAS were performed to identify variants associated with gout compared with normouricaemic controls using SU <6.0 mg/dL and <7.0 mg/dL thresholds, respectively.

RESULTS

Thirteen independent single nucleotide polymorphisms (SNPs) in ABCG2, SLC2A9, SLC22A11, GCKR, MEPE, PPM1K-DT, LOC105377323 and ADH1B reached genome-wide significance and replicated as predictors of AH to gout transition. Twelve of 13 associations were novel for this transition, and rs1229984 (ADH1B) was identified as GWAS locus for gout for the first time. The best PRS model was generated from association data of 17 SNPs; and had predictive ability of 58.5% that increased to 69.2% on including demographic factors. Two novel SNPs rs760077(MTX1) and rs3800307(PRSS16) achieved GWAS significance for association with gout compared with normouricaemic controls using both SU thresholds.

CONCLUSION

The association of urate transporters with gout supports the central role of hyperuricaemia in its pathogenesis. Larger GWAS are required to identify if variants in inflammatory pathways contribute to progression from AH to gout.

Gout, Hyperuricaemia and Crystal-Associated Disease Network (G-CAN) common language definition of gout

Objective

To develop a Gout, Hyperuricaemia and Crystal-Associated Disease Network (G-CAN) common language definition of gout, with the goal of increasing public understanding and awareness, and ensure consistent and understandable messages about gout.

Methods

A G-CAN working group that included patients, physicians and nongovernmental organisation (NGO) representatives was formed to develop a common language definition of gout for use with the public, media, healthcare providers and stakeholders. A literature search and interviews with patients, healthcare workers and stakeholders informed development of the definition. Following consultation with G-CAN members and partners, the definition was endorsed by the G-CAN board.

Results

The G-CAN common language definition of gout describes the epidemiology, pathophysiology, symptoms and impact, risk factors, comorbidities, management and healthcare and workforce considerations. Detailed information is provided to support the content of the definition. After the publication of the English-language version, the definition will be available for translation into other languages by G-CAN members.

Conclusion

G-CAN has developed a concise and easily understandable statement describing gout in language that can be used in conversations with the lay public, media, NGOs, funders, healthcare providers and other stakeholders.

Genetic and Physiological Effects of Insulin on Human Urate Homeostasis

Insulin and hyperinsulinemia reduce renal fractional excretion of urate (FeU) and play a key role in the genesis of hyperuricemia and gout, via uncharacterized mechanisms. To explore this association further we studied the effects of genetic variation in insulin-associated pathways on serum urate (SU) levels and the physiological effects of insulin on urate transporters. We found that urate-associated variants in the human insulin (INS), insulin receptor (INSR), and insulin receptor substrate-1 (IRS1) loci associate with the expression of the insulin-like growth factor 2, IRS1, INSR, and ZNF358 genes; additionally, we found genetic interaction between SLC2A9 and the three loci, most evident in women. We also found that insulin stimulates the expression of GLUT9 and increases [14C]-urate uptake in human proximal tubular cells (PTC-05) and HEK293T cells, transport activity that was effectively abrogated by uricosurics or inhibitors of protein tyrosine kinase (PTK), PI3 kinase, MEK/ERK, or p38 MAPK. Heterologous expression of individual urate transporters in Xenopus oocytes revealed that the [14C]-urate transport activities of GLUT9a, GLUT9b, OAT10, OAT3, OAT1, NPT1 and ABCG2 are directly activated by insulin signaling, through PI3 kinase (PI3K)/Akt, MEK/ERK and/or p38 MAPK. Given that the high-capacity urate transporter GLUT9a is the exclusive basolateral exit pathway for reabsorbed urate from the renal proximal tubule into the blood, that insulin stimulates both GLUT9 expression and urate transport activity more than other urate transporters, and that SLC2A9 shows genetic interaction with urate-associated insulin-signaling loci, we postulate that the anti-uricosuric effect of insulin is primarily due to the enhanced expression and activation of GLUT9.

Changing paradigms in the management of gout

The incidence and prevalence of gout have increased, as have comorbid obesity, diabetes mellitus, hypertension, chronic kidney and cardiovascular disease. Gout is now the commonest type of inflammatory arthritis despite availability of safe, effective and potentially 'curative' urate-lowering drugs. Modern imaging studies show that gout is a chronic inflammatory crystal deposition disorder even at the first acute attack and they illuminate the need to eliminate urate crystals by continuing reduction of the serum urate below its solubility threshold. Clinical outcomes, adherence to therapy and quality of gout care in primary care and hospital practice can be greatly improved by better use of allopurinol and flare prophylaxis, greater patient engagement, education and follow-up, and by nurse-led models of care that employ a 'treat-to-target' principle (SUA< 360 or 300µmol/l). Advances in understanding the physiology and genetic control of urate transport in the kidney and gut have led to novel, more selective uricosuric drugs, and basic research on mediators of urate crystal-induced inflammation has pointed to alternative therapeutic targets for treating and preventing gout flares. Current guidelines for the management of gout and indications for the use of some more recently introduced drugs; febuxostat, lesinurad, pegloticase and interleukin-1 antagonists are also briefly reviewed.

Urate-induced epigenetic modifications in myeloid cells

OBJECTIVES

Hyperuricemia is a metabolic condition central to gout pathogenesis. Urate exposure primes human monocytes towards a higher capacity to produce and release IL-1β. In this study, we assessed the epigenetic processes associated to urate-mediated hyper-responsiveness.

METHODS

Freshly isolated human peripheral blood mononuclear cells or enriched monocytes were pre-treated with solubilized urate and stimulated with LPS with or without monosodium urate (MSU) crystals. Cytokine production was determined by ELISA. Histone epigenetic marks were assessed by sequencing immunoprecipitated chromatin. Mice were injected intraarticularly with MSU crystals and palmitate after inhibition of uricase and urate administration in the presence or absence of methylthioadenosine. DNA methylation was assessed by methylation array in whole blood of 76 participants with normouricemia or hyperuricemia.

RESULTS

High concentrations of urate enhanced the inflammatory response in vitro in human cells and in vivo in mice, and broad-spectrum methylation inhibitors reversed this effect. Assessment of histone 3 lysine 4 trimethylation (H3K4me3) and histone 3 lysine 27 acetylation (H3K27ac) revealed differences in urate-primed monocytes compared to controls. Differentially methylated regions (e.g. HLA-G, IFITM3, PRKAB2) were found in people with hyperuricemia compared to normouricemia in genes relevant for inflammatory cytokine signaling.

CONCLUSION

Urate alters the epigenetic landscape in selected human monocytes or whole blood of people with hyperuricemia compared to normouricemia. Both histone modifications and DNA methylation show differences depending on urate exposure. Subject to replication and validation, epigenetic changes in myeloid cells may be a therapeutic target in gout.

Function of Uric Acid Transporters and Their Inhibitors in Hyperuricaemia

Disorders of uric acid metabolism may be associated with pathological processes in many diseases, including diabetes mellitus, cardiovascular disease, and kidney disease. These diseases can further promote uric acid accumulation in the body, leading to a vicious cycle. Preliminary studies have proven many mechanisms such as oxidative stress, lipid metabolism disorders, and rennin angiotensin axis involving in the progression of hyperuricaemia-related diseases. However, there is still lack of effective clinical treatment for hyperuricaemia. According to previous research results, NPT1, NPT4, OAT1, OAT2, OAT3, OAT4, URAT1, GLUT9, ABCG2, PDZK1, these urate transports are closely related to serum uric acid level. Targeting at urate transporters and urate-lowering drugs can enhance our understanding of hyperuricaemia and hyperuricaemia-related diseases. This review may put forward essential references or cross references to be contributed to further elucidate traditional and novel urate-lowering drugs benefits as well as provides theoretical support for the scientific research on hyperuricemia and related diseases.

Causal Associations of Urate With Cardiovascular Risk Factors: Two-Sample Mendelian Randomization

Background

Mendelian Randomization (MR) studies show conflicting causal associations of genetically predicted serum urate with cardiovascular risk factors (i.e., hypertension, diabetes, lipid profile, and kidney function). This study aimed to robustly investigate a causal relationship between urate and cardiovascular risk factors considering single nucleotide polymorphisms (SNPs) as instrumental variables using two-sample MR and various sensitivity analyses.

Methods

Data on SNP-urate associations were taken from the Global Urate Genetics Consortium and data on SNP-cardiovascular risk factor associations were taken from various consortia/UK Biobank. SNPs were selected by statistically and biologically driven approaches as instrumental variables. Various sensitivity analyses were performed using different MR methods including inverse variance weighted, MR-Egger, weighted median/mode, MR-PRESSO, and the contamination mixture method.

Results

The statistically driven approach showed significant causal effects of urate on HDL-C and triglycerides using four of the six MR methods, i.e., every 1 mg/dl increase in genetically predicted urate was associated with 0.047 to 0.103 SD decrease in HDL-C and 0.034 to 0.207 SD increase in triglycerides. The biologically driven approach to selection of SNPs from ABCG2, SLC2A9, SLC17A1, SLC22A11, and SLC22A12 showed consistent causal effects of urate on HDL-C from all methods with 0.038 to 0.057 SD decrease in HDL-C per 1 mg/dl increase of urate, and no evidence of horizontal pleiotropy was detected.

Conclusion

Our study suggests a significant and robust causal effect of genetically predicted urate on HDL-C. This finding may explain a small proportion (7%) of the association between increased urate and cardiovascular disease but points to urate being a novel cardiac risk factor.

Understanding the effect of smoking and drinking behavior on Parkinson's disease risk: a Mendelian randomization study

Previous observational studies have identified correlations between Parkinson's disease (PD) risk and lifestyle factors. However, whether or not those associations are causal remains unclear. To infer causality between PD risk and smoking or alcohol intake, we conducted a two-sample Mendelian randomization study using genome-wide association study summary statistics from the GWAS & Sequencing Consortium of Alcohol and Nicotine use study (1.2 million participants) and the latest meta-analysis from the International Parkinson's Disease Genomics Consortium (37,688 PD cases and 18,618 proxy-cases). We performed sensitivity analyses, including testing for pleiotropy with MR-Egger and MR-PRESSO, and multivariable MR modeling to account for the genetic effects of competing substance use traits on PD risk. Our results revealed causal associations of alcohol intake (OR 0.79; 95% CI 0.65-0.96; p = 0.021) and smoking continuation (which compares current vs. former smokers) (OR 0.64; 95% CI 0.46-0.89; p = 0.008) with lower PD risk. Multivariable MR analyses showed that the causal association between drinks per week and PD is unlikely due to confounding by smoking behavior. Finally, frailty analyses suggested that the causal effects of both alcohol intake and smoking continuation on PD risk estimated from MR analysis are not explained by the presence of survival bias alone. Our findings support the role of smoking as a protective factor against PD, but only when comparing current vs. former smokers. Similarly, increased alcohol intake had a protective effect over PD risk, with the alcohol dehydrogenase 1B (ADH1B) locus as a potential candidate for further investigation of the mechanisms underlying this association.

Genomic dissection of 43 serum urate-associated loci provides multiple insights into molecular mechanisms of urate control

High serum urate is a prerequisite for gout and associated with metabolic disease. Genome-wide association studies (GWAS) have reported dozens of loci associated with serum urate control; however, there has been little progress in understanding the molecular basis of the associated loci. Here, we employed trans-ancestral meta-analysis using data from European and East Asian populations to identify 10 new loci for serum urate levels. Genome-wide colocalization with cis-expression quantitative trait loci (eQTL) identified a further five new candidate loci. By cis- and trans-eQTL colocalization analysis, we identified 34 and 20 genes, respectively, where the causal eQTL variant has a high likelihood that it is shared with the serum urate-associated locus. One new locus identified was SLC22A9 that encodes organic anion transporter 7 (OAT7). We demonstrate that OAT7 is a very weak urate-butyrate exchanger. Newly implicated genes identified in the eQTL analysis include those encoding proteins that make up the dystrophin complex, a scaffold for signaling proteins and transporters at the cell membrane; MLXIP that, with the previously identified MLXIPL, is a transcription factor that may regulate serum urate via the pentose-phosphate pathway and MRPS7 and IDH2 that encode proteins necessary for mitochondrial function. Functional fine mapping identified six loci (RREB1, INHBC, HLF, UBE2Q2, SFMBT1 and HNF4G) with colocalized eQTL containing putative causal SNPs. This systematic analysis of serum urate GWAS loci identified candidate causal genes at 24 loci and a network of previously unidentified genes likely involved in control of serum urate levels, further illuminating the molecular mechanisms of urate control.

An update of genetics, co-morbidities and management of hyperuricaemia

Hyperuricaemia (HU) caused by disorders of purine metabolism is a metabolic disease. A number of epidemiological reports have confirmed that HU is correlated with multiple disorders, such as chronic kidney diseases, cardiovascular disease and gout. Recent studies showed that the expression and functional changes of uric acid transporters, including URAT1, GLUT9 and ABCG2, were associated with HU. Moreover, a large number of genome-wide association studies have shown that these transporters' dysfunction leads to HU. In this review, we describe the recent progress of aetiology and related transporters of HU, and we also summarise the common co-morbidities possible mechanisms, as well as the potential pharmacological and non-pharmacological treatment methods for HU, aiming to provide new ideas for the treatment of HU.

The biology of urate

Urate is the end-product of the purine metabolism in humans. The dominant source of urate is endogenous purines and the remainder comes through diet. Approximately two thirds of urate is eliminated via the kidney with the rest excreted in the feces. While the transporter BCRP, encoded by ABCG2, has been found to play a role in both the gut and kidney, SLC22A12 and SLC2A9 encoding URAT1 and GLUT9, respectively, are the two transporters best characterized. Only 8-12% of the filtered urate is excreted by the kidney. Renal elimination of urate depends substantially on specific transporters, including URAT1, GLUT9 and BCRP. Studies that have assessed the biologic effects of urate have produced highly variable results. Although there is a suggestion that urate may have anti-oxidant properties in some circumstances, the majority of evidence indicates that urate is pro-inflammatory. Hyperuricemia can result in the formation of monosodium urate (MSU) crystals that may be recognized as danger signals by the immune system. This immune response results in the activation of the NLRP3 inflammasome and ultimately in the production and release of interleukin-1β, and IL-18, that mediate both inflammation, pyroptotic cell death, and necroinflammation. It has also been demonstrated that soluble urate mediates effects on the kidney to induce hypertension and can induce long term epigenetic reprogramming in myeloid cells to induce "trained immunity." Together, these sequelae of urate are thought to mediate most of the physiological effects of hyperuricemia and gout, illustrating this biologically active molecule is more than just an "end-product" of purine metabolism.

Genetic Predisposition to Type 2 Diabetes and Insulin Levels Is Positively Associated With Serum Urate Levels

PURPOSE

Previous epidemiological evidence showed that type 2 diabetes (T2D) is related with gout. However, the causality and the direction of this association are still not definitely elucidated. We investigated bidirectional associations of T2D and glycemic traits with serum urate concentrations and gout using a Mendelian randomization approach.

METHODS

Summary statistics from the large-scale genomewide association studies conducted for T2D (Ncase = 62 892, Ncontrol = 596 424), fasting glucose (N = 133 010), fasting insulin (N = 133 010), hemoglobin A1c (N = 123 665), homeostasis model assessment of insulin resistance (N = 46 186), urate (N = 110 347), and gout (Ncase = 2115, Ncontrol = 67 259) among participants of European ancestry were analyzed. For each trait of interest, independent genomewide significant (P < 5 × 10-8) single nucleotide polymorphisms were selected as instrumental variables. The inverse-variance weighted method was used for the primary analyses.

RESULTS

Genetic predisposition to higher risk of T2D [beta = 0.042; 95% confidence interval (CI) = 0.016-0.068; P = 0.002] and higher levels of fasting insulin (beta = 0.756; 95% CI = 0.408-1.102; P = 1.96e-05) were significantly associated with increased serum urate concentrations. Moreover, we found suggestively significant evidence supporting a causal role of fasting insulin on risk of developing gout (odds ratio = 3.06; 95% CI = 0.88-10.61; P = 0.078). In the reverse direction analysis, genetic predisposition to both urate and gout were not associated with T2D or any of 4 glycemic traits being investigated.

CONCLUSIONS

This study provides supportive evidence on causal associations of T2D and fasting insulin with serum urate concentrations and a suggestive association of fasting insulin with risk of gout. Future research is required to examine the underlying biological mechanisms on such relationships.

Serum urate and lung cancer: a cohort study and Mendelian randomization using UK Biobank

BACKGROUND

Serum urate is the most abundant small molecule with antioxidant properties found in blood and the epithelial lining fluid of the respiratory system. Moderately raised serum urate is associated with lower rates of lung cancer and COPD in smokers but whether these relationships reflect antioxidant properties or residual confounding is unknown.

METHODS

We investigated the observational and potentially causal associations of serum urate with lung cancer incidence and FEV1 using one-sample Mendelian randomization (MR) and the UK Biobank resource. Incident lung cancer events were identified from national cancer registries as FEV1 was measured at baseline. Observational and genetically instrumented incidence rate ratios (IRRs) and risk differences per 10,000 person-years (PYs) by smoking status were estimated.

RESULTS

The analysis included 359,192 participants and 1,924 lung cancer events. The associations between measured urate levels and lung cancer were broadly U-shaped but varied by sex at birth with the strongest associations in current smoking men. After adjustment for confounding variables, current smoking men with low serum urate (100 µmol/L) had the highest predicted lung cancer incidence at 125/10,000 PY (95%CI 56-170/10,000 PY) compared with 45/10,000 PY (95%CI 38-47/10,000 PY) for those with the median level (300 µmol/L). Raised measured urate was associated with a lower baseline FEV1. The MR results did not support a causal relationship between serum urate and lung cancer or FEV1.

CONCLUSIONS

We found no evidence that serum urate is a modifiable risk factor for respiratory health or lung cancer.

Higher Serum Urate Levels Are Associated With an Increased Risk for Sudden Cardiac Death

OBJECTIVE

To determine the association of serum urate (SU) levels with sudden cardiac death and incident coronary heart disease (CHD), separately, among adults without a history of CHD.

METHODS

We conducted a case-cohort analysis of Black and White participants aged ≥ 45 years enrolled in the REason for Geographic And Racial Differences in Stroke (REGARDS) study without a history of CHD at baseline between 2003 and 2007. Participants were followed for sudden cardiac death or incident CHD (i.e., myocardial infarction [MI] or death from CHD excluding sudden cardiac death) through December 31, 2013. Baseline SU was measured in a random sample of participants (n = 840) and among participants who experienced sudden cardiac death (n = 235) or incident CHD (n = 851) during follow-up.

RESULTS

Participants with higher SU levels were older and more likely to be male or Black. The crude HR (95% CI) per 1 mg/dL higher SU level was 1.26 (1.14-1.40) for sudden cardiac death and 1.17 (1.09-1.26) for incident CHD. After adjustment for age, sex, race, and cardiovascular risk factors, the HR (95% CI) per 1 mg/dL higher SU level was 1.19 (1.03-1.37) for sudden cardiac death and 1.05 (0.96-1.15) for incident CHD. HRs for sudden cardiac death were numerically higher among participants aged 45-64 vs ≥ 65 years, without vs with diabetes, and among those of White vs Black race, although P values for effect modification were all ≥ 0.05.

CONCLUSION

Higher SU levels were associated with an increased risk for sudden cardiac death but not with incident CHD.