Asymptomatic Hyperuricemia and Metabolically Unhealthy Obesity: A Cross-Sectional Analysis in the Tianning Cohort

Phosphorus modifies the association between body mass index and uric acid: Results from NHANES 2007-2018

INTRODUCTION

Studies in recent years have shown that high uric acid causes harm to the human body, which has become a serious public health problem. Elevated serum uric acid has been shown to be associated with obesity, but the relationship between BMI and uric acid (UA) remains controversial. Although the association between BMI and UA has been well studied, the effect of phosphorus levels in vivo on this association remains unclear. This study aimed to determine the relationship between BMI and serum uric acid and the effect of phosphorus on the relationship between the two.

RESEARCH DESIGN AND METHODS

The present study analyzed data from the National Health and Nutrition Examination Survey (NHANES) continuous 2007-2018 cycle. We included 10786 participants aged 20 years and over. Multivariable linear regression was performed to assess the association between BMI and serum uric acid. phosphorus was stratified into low phosphorus (<3.3 mg/dl), middle phosphorus (3.3-3.9 mg/dl) and high phosphorus (>3.9 mg/dl). Correction of the effect of phosphorus was assessed by testing the interaction between BMI and UA in multivariate linear regression.

RESULTS

In this cross-sectional study, we found that BMI was positively associated with UA in the female population but not significantly in the male population or in the total population. In multiple regression analysis, UA was 0.51 higher in the highest female BMI group than in the lowest group (p = 0.0001). The relationship between BMI and UA differed significantly by gender under the influence of phosphorus, with men and women in Model II having a greater elevation of UA in men than in women within most groups. (BMI >30, phosphorus >3.9 mg/dl, β:0.83 95% CI: 0.43, 1.23 vs β: 0.79 95% CI: 0.30, 1.29). In addition, phosphorus significantly altered the positive association between BMI and UA in most models.

CONCLUSION

Our results indicate significant associations between BMI and uric acid in women, with higher BMI values likely to be associated with a higher risk of hyperuricemia, suggesting that uric acid levels in obese people should be closely monitored in clinical practice. Phosphorus and BMI have an interactive effect in elevating UA and should be noted as indicators of phosphorus in clinical practice.

Bariatric Surgery and Its Metabolic Echo Effect on Serum Uric Acid Levels

Bariatric surgery (BS) has been a significant means of reducing weight in obese individuals. The metabolic changes after bariatric surgery are crucial as they extend its advantages beyond weight loss. As its name implies, "metabolic surgery" also addresses obesity-related metabolic concerns. Bariatric surgery has always been associated with lessened serum uric acid (SUA) levels. In this review, we examined current studies to understand how surgical therapies impact serum uric acid levels. Strongly minded on the extent and timing of changes in the level of serum uric acid after bariatric surgeries. We conducted a comprehensive search for relevant current studies in PubMed, Google Scholar, JAMA, and the Cochrane Library until February 1, 2024. We aimed to analyze the metabolic advantages of bariatric surgery, focusing on its function in treating hyperuricemia and lowering the risk of associated disorders. Our review elaborates on factors contributing to decreased serum uric acid levels after bariatric surgery, such as alterations in renal function, insulin sensitivity, and inflammatory markers.

The association between BMI and serum uric acid is partially mediated by gut microbiota

Obesity is a risk factor for the development of hyperuricemia, both of which were related to gut microbiota. However, whether alterations in the gut microbiota lie in the pathways mediating obesity's effects on hyperuricemia is less clear. Body mass index (BMI) and serum uric acid (SUA) were separately important indicators of obesity and hyperuricemia. Our study aims to investigate whether BMI-related gut microbiota characteristics would mediate the association between BMI and SUA levels. A total of 6,280 participants from Guangdong Gut Microbiome Project were included in this study. Stool samples were collected for 16S rRNA gene sequencing. The results revealed that BMI was significantly and positively associated with SUA. Meanwhile, BMI was significantly associated with the abundance of 102 gut microbial genera, 16 of which were also significantly associated with SUA. The mediation analysis revealed that the association between BMI and SUA was partially mediated by the abundance of Proteobacteria (proportion mediated: 0.94%, P < 0.05). At the genus level, 25 bacterial genera, including Ralstonia, Oscillospira, Faecalibacterium, etc., could also partially mediate the association of BMI with SUA (the highest proportion is mediated by Ralstonia, proportion mediated: 2.76%, P < 0.05). This study provided evidence for the associations among BMI, gut microbiota, and SUA, and the mediation analysis suggested that the association of BMI with SUA was partially mediated by the gut microbiota. IMPORTANCE Using 16S rRNA sequencing analysis, local interpretable machine learning technique analysis and mediation analysis were used to explore the association between BMI with SUA, and the mediating effects of gut microbial dysbiosis in the association were investigated.

Association between metabolic obesity phenotype, transition of metabolic phenotypes and the risk of hyperuricemia in Chinese adults: A cohort study

Prospective evidence on the association of obesity and metabolic health status and its transition over time with the risk of hyperuricemia in the Chinese population is limited. This study aims to investigate the phenotypic transition characteristics of metabolic obesity in Chinese adults and its association with hyperuricemia. Using the China Health and Retirement Longitudinal Survey (CHARLS) survey data in 2011 and 2015, 6059 adults aged ≥ 18 years were selected as the research people. The participants' general information, living habits, blood sample testing, and blood uric acid testing data during follow-up were extracted. According to body weight and metabolic health status, obesity phenotypes were divided into: metabolically normal weight group (MHNW), metabolically normal overweight/obesity group (MHOWO); metabolically abnormal normal weight group (MUNW); metabolically abnormal overweight/obese group (MUHOWO). Multiple linear regression was used to evaluate the correlation between metabolic obesity phenotype and serum uric acid level, and logistic regression model was used to analyze the association of metabolic obesity phenotype and transition with the risk of hyperuricemia. The average age of all subjects was (58.62 ± 8.93) years old, and 42.1% were male. The MHOWO phenotype was present in 19.2% of the general population and 48.6% of the baseline who were overweight or obese population. During the 4-year follow-up period, only 10.7% of participants with MHNW at baseline converted to MHOWO. Among MHOWO participants, 21.2% converted to MUHOWO. MHOWO also increased the risk of hyperuricemia (OR, 1.57; 95% CI 1.15-2.13; P = .004), both in obese and normal-weight individuals, even when metabolic status changed from unhealthy to healthy. Risk of hyperuricemia was high among those who remained metabolically unhealthy but of normal weight (OR, 3.09; 95% CI 1.51-6.30; P = .001). MHOWO also increases the risk of hyperuricemia, and MHOWO remains stable or changes to MUHOWO, which increases the risk of hyperuricemia. Therefore, close attention should be paid to the transition of metabolic health status over time, and individualized prevention strategies should be focused on metabolically unhealthy and obese individuals.

The Association Between Hyperuricemia and Obesity Metabolic Phenotypes in Chinese General Population: A Retrospective Analysis

Purpose

Serum uric acid (UA) not only affects the development of obesity but also alters the metabolic status in obese subjects; thus we investigated the relationship between serum UA and the overweight/obese metabolic phenotypes.

Methods

The demographic, biochemical, and hematological data were collected for 12,876 patients undergoing routine physical examination, and 6,912 participants were enrolled in our study. Participants were classified into four obesity metabolic phenotypes according to their BMI and the presence of metabolic syndrome: metabolically healthy overweight/obese (MHOO), metabolically healthy and normal weighted (MHNW), metabolically abnormal and overweight/obese (MAOO), and metabolically abnormal but normal weighted (MANW). Univariate and multivariate logistic regression analysis, stratified analysis, and also interaction analysis were conducted to analyze the relationship between serum UA and obesity metabolic phenotypes.

Results

Multivariable logistic regression analysis showed that hyperuricemia was positively associated with MHOO, MANW, and MAOO phenotypes relative to MHNW. After adjusting for the confounding factors, the odds ratios (OR) for individuals with hyperuricemia to be MHOO, MANW, and MAOO phenotypes were 1.86 (1.42–2.45), 2.30 (1.44–3.66), and 3.15 (2.34–4.24), respectively. The ORs for having MHOO, MANW, and MAOO increased 6% [OR: 1.06 (1.05–1.07), P &lt; 0.0001], 5% [OR: 1.05 (1.03–1.07), P &lt; 0.0001], and 11% [OR: 1.11 (1.10–1.13), P &lt; 0.0001] for each 10 unit (μmol/L) of increase in serum UA level. Stratification analysis as well as an interaction test showed that sex and age did not interfere with the association of hyperuricemia with each metabolic phenotype. In terms of the components of the metabolic syndrome, after adjusting for other confounding factors including all of the metabolic indicators except itself, hyperuricemia was positively associated with increased BMI [OR: 1.66 (1.32–2.09), P &lt; 0.0001], hypertriglyceridemia [OR: 1.56 (1.21–2.02), P = 0.0006], and hypertension [OR: 1.22 (1.03–1.46), P = 0.0233], while it had no significant association with hyperglycemia and low HDL-C (all P &gt; 0.05).

Conclusion

In our study, we discovered that hyperuricemia was positively associated with MHOO, MANW, and MAOO phenotypes, and this relationship was independent of sex and age.

Elevated Uric Acid Mediates the Effect of Obesity on Hypertension Development: A Causal Mediation Analysis in a Prospective Longitudinal Study

Objective

Although elevated uric acid is associated with obesity and considered a predictor of hypertension, the causal linkage between the three metabolic conditions is not very clear. We aim to examine whether elevated uric acid mediates the effects of obesity on hypertension development.

Methods

A total of 1984 participants (mean aged 53 years, 62.10% female) with repeated measurements of obesity, blood pressure, and uric acid 4 years apart in the Gusu cohort were included. We first applied cross-lagged panel analysis and bidirectional association analysis to delineate the temporal association between obesity and hyperuricemia. Then, a causal mediation model was constructed to further examine the causal role of hyperuricemia in the linkage between obesity and hypertension. Age, sex, education, cigarette smoking, alcohol consumption, fasting blood glucose, and lipids were adjusted.

Results

The cross-lagged panel analysis demonstrated that the relationship from baseline obesity to follow-up hyperuricemia was stronger than that from baseline hyperuricemia to follow-up obesity (β: 0.09 vs 0.06, P<0.01 for BMI, β: 0.13 vs 0.07, P<0.01 for WC). Bidirectional association analysis found that baseline obesity predicted the risk of incident hyperuricemia (OR = 1.09, P<0.01 for BMI, OR = 1.05, P<0.01 for WC), but the other directional association was not statistically significant (all P>0.05). The causal mediation analysis found that hyperuricemia partially mediated the association of baseline BMI (mediate proportion: 3.09%, 95% CI: 0.97%~6.00% for SBP, 3.74%, 95% CI: 1.55%~7.00% for DBP) and baseline WC (mediate proportion: 5.56%, 95% CI: 2.01%~11.00% for SBP, 5.81%, 95% CI: 2.59%~10.00% for DBP) with follow-up blood pressures.

Conclusion

Obesity preceded hyperuricemia and the latter partially mediated the relationship between obesity and hypertension, independent of behavioral and other metabolic factors.

Joint Effect of Beer, Spirits Intake, and Excess Adiposity on Hyperuricemia Among Chinese Male Adults: Evidence From the China National Health Survey

Alcohol intake and excess adiposity are associated with serum uric acid (SUA), but their interaction effect on hyperuricemia (HUA) remains unclear. Using data from the China National Health Survey (CNHS) (2012-2017), we analyzed the additive interaction of beer, spirits intake, excess adiposity [measured by body mass index (BMI), body fat percentage (BFP), and visceral fat index (VFI)] with HUA among male participants aged 20-80 from mainland China. The relative excess risk due to interaction (RERI), the attributable proportion due to interaction (AP), and the synergy index (SI) were calculated to assess the interaction effect on the additive scale. Both RERI and AP larger than 0 and SI larger than 1 indicate a positive additive interaction. Among 12,592 male participants, the mean SUA level was 367.1 ± 85.5 μmol/L and 24.1% were HUA. Overweight/obese men who were presently drinking spirits had an odds ratio (OR) of 3.20 (95%CI: 2.71-3.79) than the never drink group, with RERI, AP, and SI of 0.45 (95%CI: 0.08-0.81), 0.14 (95%CI: 0.03-0.25), and 1.25 (95%CI: 1.02-1.54), respectively. However, although combined exposures on beer intake and excess adiposity had the highest OR compared with no beer intake and nonobese participants, there was no additive interaction, with RERI, AP, and SI in the overweight/obesity and the beer intake group of 0.58 (-0.41-1.57), 0.17 (-0.08-0.41), and 1.30 (0.85-1.97), respectively. Other excess adiposity indexes revealed similar estimates. Our findings suggested that the exposures of both excess adiposity and alcohol drink could result in an additive interaction effect on HUA: the combined risk of excess adiposity with spirits intake but not with beer was greater than the sum of the effects among Chinese male adults.

Association between hyperuricemia and metabolic syndrome: A cross-sectional study in Tibetan adults on the Tibetan plateau

PURPOSE

This study aimed to assess the relationship of serum uric acid with metabolic syndrome and its components in Tibetan adults on the Tibetan plateau.

METHODS

A total of 307 participants were enrolled in this study and biochemical parameters including serum uric acid, fasting plasma glucose, white blood cell, lymphocyte count, mononuclear cells, alanine aminotransferase, aspartate aminotransferase, creatinine, and lipid profile were analyzed using standard methods. The IDF criteria were applied to define metabolic syndrome. The association of serum uric acid with metabolic syndrome and its components was evaluated by multivariable logistic regression models.

RESULTS

The overall prevalence of metabolic syndrome was 17.3% (53/307) with 19.6% (31/158) in females and 14.8% (22/149) in male participants. The prevalence of hyperuricemia was 40.7% (125/307) with significant differences between the male (53.7%,80/149) and female (28.5%,45/158) groups. In regression analysis, we observed that the risk of MetS was higher in participants in the hyperuricemia group (adjusted OR, 4.01; 95% CI, 2.02~7.99) compared with those in the normouricemia group. After adjusting for all confounding factors, a 9% higher risk of MetS could be shown in participants with SUA increased per 10umol/L (adjusted OR, 1.09; 95% CI, 1.04~1.14). These relationships were not affected by sex or age (p >0.05). After adjusting for the confounding factors, hyperuricemia is positively associated with abdominal obesity (adjusted OR, 2.53; 95% CI, 1.41~4.53), elevated blood pressure (adjusted OR, 2.61; 95% CI, 1.37~4.97), and elevated triglycerides(adjusted OR, 2.47; 95% CI, 1.09~5.57).

CONCLUSIONS

In our study, hyperuricemia is significantly associated with the prevalence of metabolic syndrome and part of its components, and these relationships are not affected by sex or age. Given the high prevalence of MetS and hyperuricemia among Tibetan adults, more studies are required to explore the role of SUA in the pathogenesis of MetS.

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.