The relative and interactive effects of urinary multiple metals exposure on hyperuricemia among urban elderly in China

Estimation of Hair Toxic and Essential Trace Element and Mineral Profiles of Patients with Chronic Gout

The objective of the present study was to evaluate hair levels of toxic and essential trace elements and minerals in male and female patients with chronic gout. A total of 223 examinees aged from 27 to 82 years old including 116 healthy controls (64 women and 52 men) and 107 patients with gout (56 women and 51 men) were enrolled in the current cross-sectional study. Analysis of hair toxic and essential trace element and mineral content was performed using inductively-coupled plasma mass-spectrometry. The obtained data demonstrate that hair B, Fe, I, and Mo levels in gout patients were 67%, 8%, 46%, and 21% higher in comparison to the respective control values. Hair Cr and V content in patients was more than twofold higher than in the controls. Hair Mg and Zn levels were found to be 34% and 11% lower when compared to the respective control values. Hair toxic metal and metalloid content was also significantly affected in gout patients. Specifically, hair Al, As, and Pb levels were 24%, 43%, and 33% higher in gout patients than in healthy controls, respectively. Analysis of covariance demonstrated that sex also had a significant influence on hair trace element and mineral levels in gout patients. Specifically, gout-associated overaccumulation of hair trace elements including was more profound in male than in female patients. It is assumed that trace element dysregulation may contribute to gout development and progression, especially in men. However, further studies are required to elucidate this association and the underlying molecular mechanisms.

Association between oxidative balance score and serum uric acid and hyperuricemia: a population-based study from the NHANES (2011-2018)

Background

Oxidative Balance Score (OBS) is a novel indicator of the overall antioxidant/oxidant balance, providing a comprehensive reflection of the body's overall oxidative stress status, with higher OBS suggesting more substantial antioxidant exposures. We aimed to investigate the possible relationship between OBS with serum uric acid (SUA) and hyperuricemia.

Methods

Data utilized in this study were sourced from the 2011-2018 National Health and Nutrition Examination Survey (NHANES). Participants under 18 years old, those with ≤16 complete data out of 20 OBS components, incomplete serum uric acid data, and missing covariates were excluded from the analysis. OBS was computed by evaluating 16 nutrients and 4 lifestyle factors, encompassing 5 pro-oxidants and 15 antioxidants, guided by a priori knowledge of their relationship with oxidative stress.

Results

A total of 1,5096 individuals were included in our analysis with 49.7% being male, and an average age of 49.05 ± 17.56 years. The mean OBS was 19.76 ± 7.17. Hyperuricemia was present in 19.28% of participants. Due to the right-skewed distribution of the OBS, a natural log transformation was applied to address this issue, and Quartiles of lnOBS 1, 2, 3, and 4 were 1.10-2.56 (N=3526), 2.64-2.94 (N=3748), 3.00-3.22 (N=4026), and 3.26-3.61 (N=3796), respectively. Multivariable logistic regression showed that higher lnOBS quantiles were correlated with lower serum uric acid levels. Compared with the lowest lnOBS quantile, participants in the highest lnOBS quantile had a significant serum uric acid decrease of 16.94 μmol/L for each unit increase in lnOBS (β=-16.94, 95% CI: -20.44, -13.45). Similar negative associations were observed in the second-highest (β=-8.07, 95% CI: -11.45, -4.69) and third-highest (β=-11.69, 95% CI: -15.05, -8.34) lnOBS quantiles. The adjusted odds ratios (ORs) for hyperuricemia in Quartiles 1, 2, 3, and 4 were 1.00, 0.84 (95% CI: 0.75, 0.95), 0.78 (95% CI: 0.69, 0.88), and 0.62 (95% CI: 0.55, 0.71), respectively. Compared to Quartile 1, participants in Quartile 4 had a 38% lower prevalence of hyperuricemia. Subgroup analysis and interaction test showed that there was a significant dependence of sex between OBS and serum uric acid (p for interaction <0.05), but not hyperuricemia (p for interaction >0.05). Subgroup analysis stratified by age, BMI, hypertension, diabetes, and hyperlipidemia showed there is no significant dependence on these negative correlations (all p for interaction >0.05).

Conclusions

The serum uric acid levels and prevalence of hyperuricemia in US adults exhibited a negative association with OBS. By exploring this connection, our research aims to gain a better understanding of how oxidative balance affects the prevalence of hyperuricemia. This could provide valuable insights for developing preventive strategies and interventions for hyperuricemia. Additional large-scale prospective studies are required to explore the role of OBS in hyperuricemia further.

Associations of urinary zinc exposure with blood lipid profiles and dyslipidemia: Mediating effect of serum uric acid

The relationship between zinc (Zn) exposure and abnormal blood lipids including dyslipidemia is contentious. Serum uric acid (SUA) has been reported to be correlated to both Zn exposure and dyslipidemia. The underlying mechanisms of Zn exposure associated with blood lipids and the mediating effects of SUA remain unclear. Therefore, this study analyzed the data from Chinese 2110 adults (mean age: 59.0 years old) in rural areas across China to explore the associations of Zn exposure with blood lipid profiles and dyslipidemia, and to further estimate the mediating effects of SUA in these relationships. The study data showed that urinary Zn was associated with increased levels of blood lipid components triglyceride (TG) and low-density lipoprotein cholesterol (LDL-C). Moreover, an increased risk of dyslipidemia was observed in the study participants who had higher urinary Zn levels. Compared with the first quartile, the fourth quartile of urinary Zn concentration corresponded to the increase of TG (β = 0.20, 95 % CI: 0.12, 0.28), LDL-C (β = 0.06, 95 % CI: 0.01, 0.10) and dyslipidemia risk (OR = 2.16, 95 % CI: 1.50, 3.10), respectively. Elevated urinary Zn was also associated with higher levels of SUA and hyperuricemia risk. The SUA levels were positively related to total cholesterol (TC), TG, LDL-C levels and dyslipidemia risk. Mediation analyses revealed that SUA mediated 31.75 %, 46.16 % and 19.25 % of the associations of urinary Zn with TG, LDL-C levels and dyslipidemia risk, respectively. The subgroup and sensitivity analyses confirmed the positive associations between urinary Zn and blood lipid profiles and the mediating effect of SUA. The national population-based study further enhanced our understanding of the associations between Zn exposure and blood lipid profiles and mediating effect of SUA among generally healthy, middle-aged, and elderly individuals.

Urinary nicotine metabolites are associated with cognitive impairment among the elderly in southern China

INTRODUCTION

This study comprehensively assessed the association between eight metabolites of urinary nicotine and cognitive impairment.

METHODS

This cross-sectional study was based on the data of Shenzhen Aging Related Disorder Cohort (SADC), including 51 elderly community data variables such as demographic characteristics, neuropsychological assessment and environmental factors, from July 2017 to November 2018. Participant's cognitive function was assessed by Mini-Mental State Examination (MMSE) scale and urinary nicotine metabolite [including cotinine N-β-D-glucuronide (CotGluc), rac 4-hydroxy-4-(3-pyridyl) butanoic acid dicyclohexylamine salt (HyPyBut), trans-3'-hydroxy cotinine O-β-D-glucuronide (OHCotGluc), and cotinine (Cot), etc.] concentrations were measured by high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS). Generalized linear models and restricted cubic spline models were used to explore the relationships between the urinary levels of nicotine metabolite and cognitive function.

RESULTS

A total of 296 individuals aged >60 years were included. Individuals in the third quartile of CotGluc had a 0.786 point (95% CI: -1.244 - -0.329) decrease or in the highest quartile of OHCotGluc had a 0.804 point (95% CI: -1.330 - -0.278) decreased in attention and calculation compared to those in the lowest quartile (all p for trend <0.05). Compared with those in the lowest quartile, individuals in the highest quartile of CotGluc, HyPyBut, OHCotGluc and Cot, respectively, corresponded to a 1.043 point (95% CI: -2.269-0.182), 1.101 points (95% CI: -2.391-0.188), 2.318 points (95% CI: -3.615 - -1.020), and 1.460 points (95% CI: -2.726 - -0.194) decreased in MMSE total score (all p for trend <0.05). A non-linear dose-response relationship between urinary levels of CotGluc, HyPyBut, OHCotGluc or Cot and cognitive function (all overall p<0.05, non-linear p<0.05). Subgroup analysis showed that urinary levels of CotGluc, OHCotGluc or Cot were significantly negatively associated with cognitive function (all p for trend <0.05) among females and non-smokers.

CONCLUSIONS

The findings highlight the public health implications of environmental tobacco smoke exposure, and effective interventions need to be performed for vulnerable populations.

Associations between blood essential metal mixture and serum uric acid: a cross-sectional study

Introduction

Although several studies have explored the associations between single essential metals and serum uric acid (SUA), the study about the essential metal mixture and the interactions of metals for hyperuricemia remains unclear.

Methods

We performed a cross-sectional study to explore the association of the SUA levels with the blood essential metal mixture, including magnesium (Mg), calcium (Ca), iron (Fe), copper (Cu), zinc (Zn), manganese (Mn) in Chinese community-dwelling adults (n=1039). The multivariable linear regression, the weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) were conducted to estimate the associations of blood essential metals with SUA levels and the BKMR model was also conducted to estimate the interactions of the essential metals on SUA.

Results

In the multivariable linear regression, the association of blood Mg, Mn, and Cu with SUA was statistically significant, both in considering multiple metals and a single metal. In WQS regression [β=13.59 (95%CI: 5.57, 21.60)] and BKMR models, a positive association was found between the mixture of essential metals in blood and SUA. Specifically, blood Mg and Cu showed a positive association with SUA, while blood Mn showed a negative association. Additionally, no interactions between individual metals on SUA were observed.

Discussion

In conclusion, further attention should be paid to the relationship between the mixture of essential metals in blood and SUA. However, more studies are needed to confirm these findings.