Refining genome-wide associated loci for serum uric acid in individuals with African ancestry

Association between mixed dioxin exposure and hyperuricemia in U.S. adults: A comparison of three statistical models

BACKGROUND

Previous studies on the relationship between dioxin exposures and hyperuricemia have usually been based on multi-chemical linear models. However, the complex nonlinear relationship and interaction between mixed dioxin exposures and hyperuricemia have seldom been studied. In this study, we applied three different statistical models to assess the joint effect of 12 dioxins on hyperuricemia.

METHODS

A total of 7 dioxin-like polychlorinated biphenyls (DL-PCBs), 3 polychlorinated dibenzo-p-dioxins (PCDDs), and 2 polychlorinated dibenzofurans (PCDFs) were measured in the serum of adults by the National Health and Nutrition Examination Survey (NHANES) from 2003 to 2004. We fitted multivariable logistic regression, weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) models to estimate the association of individual and mixed dioxin exposures with hyperuricemia.

RESULTS

Among the 1008 individuals included in our analysis, 20.04% had hyperuricemia. In the multivariable logistic regression established for each single dioxin, PCB28, PCB74, PCB105, PCB118, and 1,2,3,4,6,7,8-HPCDD were positively associated with hyperuricemia. With including all dioxins in the multivariable logistic regression model simultaneously, only PCB28 and 1,2,3,4,6,7,8-HPCDD were positively associated with hyperuricemia. In the WQS regression model, the WQS index was significantly associated (OR (95% CI): 2.32 (1.26, 4.28)) with hyperuricemia, and 1,2,3,4,6,7,8-HPCDD (weighted 0.22) had the largest contribution. In BKMR analysis, a significant positive association was found between mixed dioxin exposure and hyperuricemia when all dioxins were at their 60th percentile or above, compared to their 50th percentile. The univariate exposure-response function showed that PCB105 and PCB118 were positively associated with hyperuricemia.

CONCLUSION

By comparing the three statistical models, we concluded that the whole-body burden of 12 dioxins was significantly positively associated with hyperuricemia. PCB105, PCB118, and 1,2,3,4,6,7,8-HPCDD played the most important roles in hyperuricemia.

Muscle Fat Content Is Strongly Associated With Hyperuricemia: A Cross-Sectional Study in Chinese Adults

Studies have indicated that the skeletal muscle mass and strength was related to serum uric acid (UA), but there is a lack of research on the association of skeletal muscle fat content with UA. The purpose of this cross-sectional study is to investigate the correlation of skeletal muscle fat index (SMFI) and hyperuricemia (HUA) in Chinese adults. 500 subjects (306 men and 194 women) were included in the study. The participants were divided into four groups according to SMFI quartiles. Pearson's correlations between SMFI and metabolic variables were calculated. Logistic regression analysis was used to estimate the association between the quartiles of SMFI and risk of hyperuricemia. UA showed a positive association with SMFI after adjusted for BMI, age and gender. A significant association between the SMFI and risk of HUA was found, the OR for HUA was 2.79 (95% CI 1.18-6.59, p<0.05) in Q2, 2.41(95% CI 1.00-5.81, p<0.05) in Q3, and 2.63 (95% CI 1.03-6.72, p<0.05) in Q4, after adjusted for BMI. In conclusion, the SMFI was significantly associated with the level of serum UA, and the higher SMFI may indicate a higher risk of HUA, independent of BMI.

A UGT1A1 variant is associated with serum total bilirubin levels, which are causal for hypertension in African-ancestry individuals

Serum bilirubin is associated with several clinical outcomes, including hypertension, type 2 diabetes (T2D), and drug metabolism. Here, we describe findings from our genome-wide association studies (GWAS) of serum (TBIL) using a generalized linear mixed model in West Africans (n = 1127), with adjustment for age, sex, body mass index, T2D, significant principal components of population structure, and cryptic relatedness. Genome-wide conditional analysis and CAVIARBF were used to fine map significant loci. The causal effect of TBIL on hypertension was assessed by Mendelian randomization (MR) using the GWAS findings as instrumental variables (IVs) in African Americans (n = 3,067). The SNP rs887829 (UGT1A1) was significantly associated with TBIL levels (effect allele (T) frequency = 0.49, β (SE) = 0.59 (0.04), p = 9.13 × 10^-54). Genome-wide conditional analysis and regional fine mapping pointed to rs887829 as a possible causal variant with a posterior inclusion probability of 0.99. The T allele of rs887829 is associated with lower hepatic expression of UGT1A1. Using rs887829 as an IV, two-stage least-squares MR showed a causal effect of bilirubin on hypertension (β = -0.76, 95% CI [-1.52, -0.01], p = 0.0459). Our finding confirms that UGT1A1 influences bilirubin levels. Notably, lower TBIL is causally associated with the increased risk of hypertension.

The Epidemiology and Genetics of Hyperuricemia and Gout across Major Racial Groups: A Literature Review and Population Genetics Secondary Database Analysis

Gout is an inflammatory condition caused by elevated serum urate (SU), a condition known as hyperuricemia (HU). Genetic variations, including single nucleotide polymorphisms (SNPs), can alter the function of urate transporters, leading to differential HU and gout prevalence across different populations. In the United States (U.S.), gout prevalence differentially affects certain racial groups. The objective of this proposed analysis is to compare the frequency of urate-related genetic risk alleles between Europeans (EUR) and the following major racial groups: Africans in Southwest U.S. (ASW), Han-Chinese (CHS), Japanese (JPT), and Mexican (MXL) from the 1000 Genomes Project. The Ensembl genome browser of the 1000 Genomes Project was used to conduct cross-population allele frequency comparisons of 11 SNPs across 11 genes, physiologically involved and significantly associated with SU levels and gout risk. Gene/SNP pairs included: ABCG2 (rs2231142), SLC2A9 (rs734553), SLC17A1 (rs1183201), SLC16A9 (rs1171614), GCKR (rs1260326), SLC22A11 (rs2078267), SLC22A12 (rs505802), INHBC (rs3741414), RREB1 (rs675209), PDZK1 (rs12129861), and NRXN2 (rs478607). Allele frequencies were compared to EUR using Chi-Square or Fisher’s Exact test, when appropriate. Bonferroni correction for multiple comparisons was used, with p < 0.0045 for statistical significance. Risk alleles were defined as the allele that is associated with baseline or higher HU and gout risks. The cumulative HU or gout risk allele index of the 11 SNPs was estimated for each population. The prevalence of HU and gout in U.S. and non-US populations was evaluated using published epidemiological data and literature review. Compared with EUR, the SNP frequencies of 7/11 in ASW, 9/11 in MXL, 9/11 JPT, and 11/11 CHS were significantly different. HU or gout risk allele indices were 5, 6, 9, and 11 in ASW, MXL, CHS, and JPT, respectively. Out of the 11 SNPs, the percentage of risk alleles in CHS and JPT was 100%. Compared to non-US populations, the prevalence of HU and gout appear to be higher in western world countries. Compared with EUR, CHS and JPT populations had the highest HU or gout risk allele frequencies, followed by MXL and ASW. These results suggest that individuals of Asian descent are at higher HU and gout risk, which may partly explain the nearly three-fold higher gout prevalence among Asians versus Caucasians in ambulatory care settings. Furthermore, gout remains a disease of developed countries with a marked global rising.

Sex Differences in Urate Handling

Hyperuricemia, or elevated serum urate, causes urate kidney stones and gout and also increases the incidence of many other conditions including renal disease, cardiovascular disease, and metabolic syndrome. As we gain mechanistic insight into how urate contributes to human disease, a clear sex difference has emerged in the physiological regulation of urate homeostasis. This review summarizes our current understanding of urate as a disease risk factor and how being of the female sex appears protective. Further, we review the mechanisms of renal handling of urate and the significant contributions from powerful genome-wide association studies of serum urate. We also explore the role of sex in the regulation of specific renal urate transporters and the power of new animal models of hyperuricemia to inform on the role of sex and hyperuricemia in disease pathogenesis. Finally, we advocate the use of sex differences in urate handling as a potent tool in gaining a further understanding of physiological regulation of urate homeostasis and for presenting new avenues for treating the constellation of urate related pathologies.