Associations of plasma multiple metals with risk of hyperuricemia: A cross-sectional study in a mid-aged and older population of China

Lv, Ziquan; Wen, Ying; Zou, Xuan; Zhou, Guohui; Cheng, Jinquan; Zhong, Danrong; Zhang, Yanwei; Yu, Shuyuan; Liu, Ning; Peng, Chaoqiong; Chen, Guomin; Zheng, Sijia; Huang, Hui; Liu, Ran; Huang, Suli

doi:10.1016/j.chemosphere.2021.132305

Cited by 26 publications

(23 citation statements)

References 73 publications

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“…A positive association between whole blood selenium and uric acid among older adults with high selenium levels was observed in the present study. Consistent with our findings, a cross-sectional study of 1,406 Han Chinese adults revealed a positive association between serum selenium and the odds of hyperuricaemia, with an OR of 1.50 (95% CI: 1.01, 2.23) ( 77 ). In addition, selenium intake exceeding the recommended amount was positively correlated with the uric acid levels in the first (mean: 53.99 μg/day) and second (mean: 58.93 μg/day) trimesters of pregnancy for 95 Polish women ( 78 ).…”

Section: Discussionsupporting

confidence: 90%

Novel Strategies for Assessing Associations Between Selenium Biomarkers and Cardiometabolic Risk Factors: Concentration, Visit-to-Visit Variability, or Individual Mean? Evidence From a Repeated-Measures Study of Older Adults With High Selenium

Zhou

Mei

et al. 2022

Front. Nutr.

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Background and AimsPrevious studies have focused only on the cardiometabolic effects of selenium concentrations. We explored whether selenium levels and their visit-to-visit variability (VVV) and individual mean (IM) are independently associated with cardiometabolic risk factors.MethodsA three-wave repeated-measures study of older adults with high selenium (n = 201) was conducted in Beijing from 2016 to 2018. Whole blood selenium and urinary selenium concentrations were measured. VVV and IM were used to profile the homeostasis of the selenium biomarkers. Four indicators, namely standard deviation, coefficient of variation, average real variability, and variability independent of the mean, were employed to characterize VVV. We considered 13 cardiometabolic factors: four lipid profile indicators, three blood pressure indices, glucose, uric acid, waistline, hipline, waist-hip ratio, and sex-specific metabolic syndrome score. Linear mixed-effects regression models with random intercepts for the participants were employed to explore the associations of the selenium concentrations, VVV, and IM with the cardiometabolic factors.ResultsThe geometric mean whole blood and urinary selenium levels were 134.30 and 18.00 μg/L, respectively. Selenium concentrations were significantly associated with numerous cardiometabolic factors. Specifically, whole blood selenium was positively associated with total cholesterol [0.22, 95% confidence interval (CI): 0.12, 0.33], low-density lipoprotein cholesterol (LDL-C; 0.28, 95% CI: 0.13, 0.42), glucose (0.22, 95% CI: 0.10, 0.34), and uric acid (0.16, 95% CI: 0.04, 0.28). After adjustment for VVV, the IM of whole blood selenium was positively correlated with total cholesterol (0.002, 95% CI: 0.001, 0.004), triglycerides (0.007, 95% CI: 0.004, 0.011), and LDL-C (0.002, 95% CI: 0.000, 0.004). However, we did not observe any robust associations between the VVV of the selenium biomarkers and cardiometabolic risk factors after adjustment for IM.ConclusionOur findings suggest that selenium concentrations and their IMs are significantly associated with cardiometabolic risk factors among older adults with high selenium. Longer repeated-measures studies among the general population are required to validate our findings and elucidate the relevant underlying mechanisms.

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Section: Discussionsupporting

confidence: 90%

Novel Strategies for Assessing Associations Between Selenium Biomarkers and Cardiometabolic Risk Factors: Concentration, Visit-to-Visit Variability, or Individual Mean? Evidence From a Repeated-Measures Study of Older Adults With High Selenium

Zhou

Mei

et al. 2022

Front. Nutr.

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“…A negative association between serum selenium level and SUA was found in a 2-year longitudinal study on patients undergoing haemodialysis (27). Wang et al found a positive linear association between plasma selenium concentration and the prevalence of hyperuricemia, but this association was diminished when a polymetallic model was utilized (28). It was found in an intervention study that dietary selenium intake was positively associated with the level of SUA in early and mid-pregnancy (29).…”

Section: A B D E Cmentioning

confidence: 99%

Associations of metal exposure with hyperuricemia and gout in general adults

Zhu

Hui

et al. 2022

Front. Endocrinol.

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BackgroundEpidemiological evidence of the associations between metal exposure and gout-related outcomes (including serum uric acid [SUA], hyperuricemia and gout) is scarce. The aim of the study is to investigate the associations of metal exposure with SUA, hyperuricemia and gout in general adults.MethodsIn this study, the exposure to five blood metals (mercury, manganese, lead, cadmium and selenium) of general adults was analyzed based on the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2018 (n = 14,871). Linear, logistic and weighted quantile sum (WQS) regression models were applied to examine the associations of blood metals with gout-related outcomes. Possible dose-response relationships were analyzed through restricted cubic spline regression.ResultsCompared with the lowest quartile of blood metals, mercury (quartile 2 and 4), lead (quartile 2, 3, and 4) and selenium (quartile 2 and 4) were found to be positively correlated with SUA and hyperuricemia. Higher levels of mercury and lead were associated with gout, but only those in the fourth quartile had statistical significance (OR [95%CI]: 1.39 [1.10-1.75] and 1.905 [1.41-2.57]) respectively). The WQS index of the blood metals was independently correlated with SUA (β [95%CI]: 0.17 [0.13-0.20]), hyperuricemia (OR [95%CI]: 1.29 [1.16-1.42]) and gout (OR [95%CI]: 1.35 [1.15-1.58]). Among them, lead was the most heavily weighted component (weight = 0.589 for SUA, 0.482 for hyperuricemia, and 0.527 for gout). In addition, restricted cubic spline regression models showed a linear association of lead with the prevalence of hyperuricemia and gout.ConclusionOur results suggested that blood metal mixtures were positively associated with gout-related outcomes, with the greatest effect coming from lead.

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“…So far the ionomics study on hyperuricemia is almost a blank. Wang et al measured the plasma levels of 13 metals in hyperuricemia patients and controls in Chinese Han adults and found that higher plasma levels of several metal ions (particularly Zn and As) and lower levels of Co might increase hyperuricemia risk ( 247 ). Ma et al reported that increased urinary levels of toxic metals (As and Cd) and decreased levels of essential metals (Co, Mn, and I) might have a positive combined effect on hyperuricemia ( 248 ).…”

Section: Recent Progress In Ionomics Of Metabolic Diseasesmentioning

confidence: 99%

Recent advances in the application of ionomics in metabolic diseases

et al. 2023

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Trace elements and minerals play a significant role in human health and diseases. In recent years, ionomics has been rapidly and widely applied to explore the distribution, regulation, and crosstalk of different elements in various physiological and pathological processes. On the basis of multi-elemental analytical techniques and bioinformatics methods, it is possible to elucidate the relationship between the metabolism and homeostasis of diverse elements and common diseases. The current review aims to provide an overview of recent advances in the application of ionomics in metabolic disease research. We mainly focuses on the studies about ionomic or multi-elemental profiling of different biological samples for several major types of metabolic diseases, such as diabetes mellitus, obesity, and metabolic syndrome, which reveal distinct and dynamic patterns of ion contents and their potential benefits in the detection and prognosis of these illnesses. Accumulation of copper, selenium, and environmental toxic metals as well as deficiency of zinc and magnesium appear to be the most significant risk factors for the majority of metabolic diseases, suggesting that imbalance of these elements may be involved in the pathogenesis of these diseases. Moreover, each type of metabolic diseases has shown a relatively unique distribution of ions in biofluids and hair/nails from patients, which might serve as potential indicators for the respective disease. Overall, ionomics not only improves our understanding of the association between elemental dyshomeostasis and the development of metabolic disease but also assists in the identification of new potential diagnostic and prognostic markers in translational medicine.

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Associations of plasma multiple metals with risk of hyperuricemia: A cross-sectional study in a mid-aged and older population of China

Cited by 26 publications

References 73 publications

Novel Strategies for Assessing Associations Between Selenium Biomarkers and Cardiometabolic Risk Factors: Concentration, Visit-to-Visit Variability, or Individual Mean? Evidence From a Repeated-Measures Study of Older Adults With High Selenium

Novel Strategies for Assessing Associations Between Selenium Biomarkers and Cardiometabolic Risk Factors: Concentration, Visit-to-Visit Variability, or Individual Mean? Evidence From a Repeated-Measures Study of Older Adults With High Selenium

Associations of metal exposure with hyperuricemia and gout in general adults

Recent advances in the application of ionomics in metabolic diseases

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