Associations between co-exposure to multiple metals and renal function: a cross-sectional study in Guangxi, China

Associations among environmental exposure to trace elements and biomarkers of early kidney damage in the pediatric population

BACKGROUND

In kidney damage, molecular changes can be used as early damage kidney biomarkers, such as Kidney Injury Molecule-1 and Neutrophil gelatinase-associated lipocalin. These biomarkers are associated with toxic metal exposure or disturbed homeostasis of trace elements, which might lead to serious health hazards. This study aimed to evaluate the relationship between exposure to trace elements and early damage kidney biomarkers in a pediatric population.

METHODS

In Tlaxcala, a cross-sectional study was conducted on 914 healthy individuals. The participants underwent a medical review and a socio-environmental questionnaire. Five early damage kidney biomarkers were determined in the urine with Luminex, and molybdenum, copper, selenium, nickel, and iodine were measured with ICP-Mass.

RESULTS

The eGFR showed a median of 103.75 mL/min/1.73 m2. The median levels for molybdenum, copper, selenium, nickel, and iodine were 24.73 ng/mL, 73.35 ng/mL, 4.78 ng/mL, 83.68 ng/mL, and 361.83 ng/mL, respectively. Except for molybdenum and nickel, the other trace elements had significant associations with the eGFR and the early kidney damage biomarkers. Additionally, we report the association of different exposure scenarios with renal parameters.

DISCUSSION

and Conclusions. Among the explored metals, exposure to Cu and iodine impairs renal function. In contrast, Se may manifest as a beneficial metal. Interactions of Mo-Se and Mo-Iodine seem to alter the expression of NGAL; Mo-Cu for CLU; Mo-Cu, Mo-Se, and Mo-iodine for Cys-C and a-1MG; and Mo-Cu and Mo-iodine for KIM-1; were noticed. Our study could suggest that trace element interactions were associated with early kidney damage biomarkers.

Analysis of relationship between mixed heavy metal exposure and early renal damage based on a weighted quantile sum regression and Bayesian kernel machine regression model

BACKGROUND

Occupation, environmental heavy metal exposure, and renal function impairment are closely related. The relationship between mixed metal exposure and chronic renal injury is inadequately described, and the interaction between each metal is poorly explored.

OBJECTIVE

This cross-sectional study assessed mixed heavy metal exposure in the general population and their relationship with early renal impairment, as well as possible interactions between metals.

METHODS

The study was conducted in two communities in Taiyuan City in northern China. Multiple linear regression, weighted quantile sum (WQS) and bayesian kernel machine regression (BKMR) regression were used to explore the relationship of mixed heavy metal exposure with indicators of early kidney injury (N-acetyl-β-D- glucosidase (UNAG), urinary albumin (UALB)). Meanwhile, BKMR was used to explore the possible interactions between mixed heavy metal and indicators of early kidney injury.

RESULTS

Based on the WQS regression results, we observed adjusted WQS coefficient β (β-WQS) of 0.711 (95% CI: 0.543, 0.879). Notably, this change was primarily driven by As (35.6%) and Cd (22.5%). In the UALB model, the adjusted β-WQS was 0.657 (95% CI: 0.567, 0.747), with Ni (30.5%), Mn (22.1%), Cd (21.2%), and As (18.6%) exhibiting higher weights in the overall effect. The BKMR results showed a negative interaction between As and other metals in the UNAG and UALB models, a positive interaction between Mn and Ni and other metals. No significant pairwise interaction was observed in the association of metals with indicators of early kidney injury.

CONCLUSION

Through multiple linear regression, WQS regression, and BKMR analyses, we found that exposure to mixed heavy metals such as Cd, Cr, Pb, Mn, As, Co and Ni was positively correlated with UNAG and UALB. Moreover, there are complex interactions between two or more heavy metals in more than one direction.

Association of urinary arsenic metabolism with type 2 diabetes and glucose homeostasis: Cross-sectional and longitudinal associations

BACKGROUND

Previous researches have assessed the relationships of urinary arsenic metabolism with type 2 diabetes (T2D) and glucose-insulin homeostasis, but the results were controversial, and potential mechanisms remain largely unclear.

OBJECTIVES

This study aimed to investigate the cross-sectional and longitudinal associations of urinary arsenic metabolism with T2D prevalence and glucose changes in relatively higher arsenic exposure, and further to evaluate the underlying roles of oxidative damage in these relationships.

METHODS

We included 796 participants at baseline, among them 509 participants were followed up after 2 years. Logistic regression model and leave-one-out approach were applied to evaluate the associations of arsenic metabolism with T2D prevalence. Linear mixed model was conducted to estimate the relationship of arsenic metabolism with glycemic changes over two years. The associations between arsenic metabolism and indicators of oxidative stress were assessed with a linear regression model. We further performed mediation analysis to investigate the role of oxidative stress in the associations of arsenic metabolism with 2-year change of glucose levels.

RESULTS

Higher urinary MMA% increased T2D prevalence and baseline glucose levels. MMA% was positively associated with 2-year change of glucose levels. Moreover, we observed significant dose-response relationship between MMA% and 8-hydroxy-2-deoxyguanosine (8-OHdG). However, the mediating role of 8-OHdG in the association of MMA% and 2-year change of glucose levels was not observed in this population.

CONCLUSIONS

In this population exposure to relatively higher arsenic levels, higher MMA% contributed to increased T2D prevalence and glucose homeostasis disorder. Arsenic metabolism also affected oxidative stress levels, especially 8-OHdG. Further studies are required to investigate the potential mechanisms.

Associations of exposure to heavy metal mixtures with kidney stone among U.S. adults: A cross-sectional study

Assessing the effects of heavy metals (HMs) on kidney stone is often limited to analyzing individual metal exposures, with studies on the effects of exposure to mixtures of HMs being scarce. To comprehensively evaluate the relationship between exposure to mixed HMs and kidney stones, we analyzed data from the National Health and Nutrition Examination Survey (NHANES) from 2007-2016, which included 7809 adults. We used multiple statistical methods, including multiple logistic regression models, weighted quantile sum (WQS) regression, quantile g-computation (qgcomp) and bayesian kernel machine regression (BKMR), to assess the association between single HM and mixed exposure to HMs and kidney stones. Firstly, in single exposure analysis, urinary cadmium (Cd) and cobalt (Co) demonstrated a positive association with the risk of kidney stones. Secondly, various other approaches consistently revealed that mixed exposure to HMs exhibited a positive association with kidney stone risk, primarily driven by Cd, Co, and barium (Ba) in urine, with these associations being particularly notable among the elderly population. Finally, both BKMR and survey-weighted generalized linear models consistently demonstrated a significant synergistic effect between urinary Co and urinary uranium (Ur) in elevating the risk of kidney stones. Overall, this study provides new epidemiological evidence that mixed exposure to HMs is associated with an increased risk of kidney stones. Further prospectively designed studies are needed to confirm these findings.

Association between multiple metal(loid)s exposure and renal function: a cross-sectional study from southeastern China

In the real world, humans are exposed to multiple metal(loid)s (designated hereafter metals) that contain essential metals as well as toxic metals. Exposure to the metal mixture was assumed to be associated with renal function impairment; however, there is no consensus on available studies. Therefore, we here explored the association between multiple metals exposure and indicators of renal function in the general population from southeastern China. A total of 11 metals with 6 human essential metals and 5 toxic metals were determined in the selected 720 subjects. In addition, serum uric acid (SUA), serum creatinine (SCR), and the estimated glomerular filtration rate (eGFR) were measured or calculated as indicators of renal function. Using multiple flexible statistical models of generalized linear model, elastic net regression, and Bayesian kernel machine regression, the joint as well as the individual effect of metals within the mixture, and the interactions between metals were explored. When exposed to the metal mixture, the statistically non-significantly increased SUA, the significantly increased SCR, and the significantly declined eGFR were observed. In addition, the declined renal function may be primarily attributed to lead (Pb), arsenic (As), and nickel (Ni) exposure. Finally, interactions, such as the synergistic effect between Pb and Mo on SUA, whereas the antagonistic effect between Ni and Cd on SCR and eGFR were identified. Our finding suggests that combined exposure to multiple metals would impair renal function. Therefore, reducing exposure to toxic heavy metals of Pb, As, and Cd and limiting exposure to the human essential metal of Ni would protect renal function.

Combined Exposure to Multiple Metals and Kidney Function in a Midlife and Elderly Population in China: A Prospective Cohort Study

[Background] Metal exposure is suspected to be correlated to kidney function. However, the combined effects of co-exposing to multiple metals, especially both toxic and protective metals, have not been completely evaluated. [Method] A prospective cohort study was conducted with the "135" cohort for the evaluation of how plasma metal levels are correlated to kidney function in a midlife and elderly community in southern China. An amount of 1368 subjects without kidney disease at baseline were enrolled in the final analysis. By using linear regression and logistic regression models, the correlation of individual metal values with renal function parameters was assessed. Measuring of the multiple metal exposure level was performed by principal component analysis (PCA). [Results] Diminished renal function, as evaluated based on fast kidney function decline, or estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m², was positively associated with the plasma concentrations of chromium and potassium, but it was negatively associated with selenium and iron (p < 0.05). In multiple-metal analyses, linear and logistic regression models showed that the iron and chromium exposure pattern had a protective effect on renal function, whereas the sodium and potassium exposure pattern and the cadmium and lead exposure pattern increased the risk for fast kidney function decline, and eGFR < 60 mL/min/1.73 m². [Conclusions] Certain metals, including chromium, potassium, selenium, and iron, were correlated with kidney function in a midlife and elderly community in China. In addition, the potential combined influences of co-exposing to multiple metals were observed.