The association between estimated glomerular filtration rate and cadmium exposure: An 8-year follow-up study

Mediation analysis for TNF-α as a mediator between multiple metal exposure and kidney function

The association between metal mixtures and kidney function has been reported. However, reports on the mechanism of metal toxicity were limited. Oxidative stress was reported as a possible cause. This study aimed to determine the association between of kidney function and metals, such as arsenic (As), cadmium (Cd), cobalt (Co), copper (Cu), lead (Pb), selenium (Se), and zinc (Zn), and to explore the possible mediating role of tumor necrosis factor alpha (TNF-α) between metal toxicity and kidney function. In this study, we recruited 421 adults from a health examination. The concentration of blood metals was analyzed using inductively coupled plasma mass spectrometry. We used linear regression models to assess the association between metals and TNF-α. Then, mediation analysis was applied to investigate the relationship between metal exposure, TNF-α, and kidney function. In univariate linear regression, blood As, Cd, Co, Cu, Pb, and Zn levels significantly increased TNF-α and decreased kidney function. Higher blood As and Pb levels significantly increased TNF-α in multivariable linear regressions after adjusting for covariates. We found that blood levels of As (coefficients = -0.021, p = 0.011), Pb (coefficients = -0.060, p < 0.001), and Zn (coefficients = -0.230, p < 0.001) showed a significant negative association with eGFR in the multiple-metal model. Furthermore, mediation analysis showed that TNF-α mediated 41.7 %, 38.8 %, and 20.8 % of blood Cd, As and Pb, respectively. Among the essential elements, TNF-α mediated 24.5 %, 21.5 % and 19.9 % in the effects of blood Co, Cu, and Zn on kidney function, respectively. TNF-α, acting as a mediator, accounted for 20.1 % of the contribution between the WQS score of metal mixtures and the eGFR (p < 0.001). This study suggested that TNF-α may be a persuasive pathway mediating the association between metals and kidney function. Inflammation and kidney injury could be the underlying mechanisms of metal exposure. However, there is still a need to clarify the biochemical mechanism in follow-up studies.

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 cadmium environmental exposure with chronic kidney disease: A systematic review and meta-analysis

BACKGROUND

Several observational studies investigated the relationship between environmental cadmium exposure and risk of chronic kidney disease (CKD). However, results from epidemiological studies are conflicting and wide variabilities have been reported.

OBJECTIVES

We conducted a meta-analysis to evaluate the relationship between environmental cadmium exposure and CKD risk, as assessed by decreased estimated Glomerular Filtration Rate (eGFR) in adults.

METHODS

PubMed, Embase and the Cochrane library databases were searched for studies published up to July 2023. A random-effects model using the restricted maximum likelihood (REML) method was used to calculate the overall estimate to assess the association between cadmium exposure and eGFR. Subgroup analysis, funnel plot, Egger's test, and the trim-and-fill method were also conducted.

RESULTS

Thirty-one articles, 3 cohorts, 2 case-control and 26 cross-sectional studies, across 8 countries, involving 195.015 participants were included. The meta-analysis demonstrated an inverse association between high cadmium exposure and eGFR levels (standardized regression coefficient β = -0.09; 95 % CI = -0.15, -0.04). The subgroup analysis showed that the inverse association was significantly higher for blood cadmium exposure (β = -0.12; 95 % CI = -0.18, -0.06) than for urinary concentrations (β = -0.04; 95 % CI: -0.10, 0.03) or dietary exposure (β = -0.03; 95 % CI = -0.19, 0.14). Stratified analysis by different study design also showed an inverse association between cadmium exposure and eGFR, more evident in the cross-sectional studies (β = -0.11; 95 % CI = -0.18, -0.03) than in the cohort (β = -0.05; 95 % CI = -0.26, 0.17) and in the case-control studies (β = -0.05; 95 % CI = -0.32, 0.21).

DISCUSSION

Our meta-analysis indicated that environmental cadmium exposure is associated with increased risk of CKD, as assessed by decreased eGFR, and this association is more evident for blood cadmium concentrations than for urinary concentrations or dietary exposure. Nevertheless, additional high quality prospective studies are needed to confirm the association between cadmium exposure and risk of CKD.

Association of exposure to multiple serum metals with the risk of chronic kidney disease in the elderly: a population-based case-control study

In the world, chronic kidney disease (CKD) has been recognized as one of the critical public health problems, and the prevalence is higher in the elderly people. However, there are few studies on the association between exposure to multiple serum metal levels and CKD. A case-control study, we established, for elderly people in Anhui Province, China, to explore the effects of different metals and analyze the effect of mixed exposure on CKD. In this study, 287 cases of CKD and 287 controls were selected in the elderly health physical examination project in Tongling City, Anhui Province. Questionnaire survey, physical examination, and blood collection were conducted. Graphite furnace atomic absorption spectrometry (GFAAS) and inductively coupled plasma optical emission spectrometry (ICP-OES) were used to measure the concentration of serum metals. After selecting by least absolute shrinkage and selection operator (LASSO), 5 metals were brought into the multi-metal model. After adjusting all potential covariates additionally, the concentrations of lead (Pb), cadmium (Cd), cobalt (Co), and manganese (Mn) were significantly associated with CKD risk, whereas Pb, Se, and Cd had significant non-linearity with CKD. Besides, patients with highest quartiles of cobalt (Co), lead (Pb), and manganese (Mn) were 1.64, 1.39, and 0.64 times more possible to have CKD, respectively, as compared with the lowest levels. In the Bayesian kernel machine regression (BKMR) model, cadmium (Cd) had a combined effect with lead (Pb) possibly. This study suggested that the CKD risk was associated with exposure of multiple metals in elderly people. The underlying mechanisms of serum metals and CKD need more experimental and prospective studies to elucidate.

Environmental Exposures and Kidney Disease

Accumulating evidence underscores the large role played by the environment in the health of communities and individuals. We review the currently known contribution of environmental exposures and pollutants on kidney disease and its associated morbidity. We review air pollutants, such as particulate matter; water pollutants, such as trace elements, per- and polyfluoroalkyl substances, and pesticides; and extreme weather events and natural disasters. We also discuss gaps in the evidence that presently relies heavily on observational studies and animal models, and propose using recently developed analytic methods to help bridge the gaps. With the expected increase in the intensity and frequency of many environmental exposures in the decades to come, an improved understanding of their potential effect on kidney disease is crucial to mitigate potential morbidity and mortality.

Associations between plasma metal levels and mild renal impairment in the general population of Southern China

BACKGROUND

Metal exposure were assumed to be closely related with declined renal function, but the conclusions were controversial. We employed diverse statistical models and assessed the association between metal mixture exposure and mild renal impairment.

METHODS

A total of 13 plasma metals were measured in 896 general population from Southern China. Subjects with estimated glomerular filtration rate within 60-89 ml/min/1.73 m² and urinary albumin-creatinine ratio <30 mg/g creatinine were defined as mild renal impairment (MRI).

RESULTS

About 31.47 % participants showed MRI. In the multivariate logistic regression models, compared with the first quartile, high levels of arsenic and molybdenum (the fourth quartile) were both associated with MRI, and the ORs (95 % CI) were 1.68 (1.05, 2.68) and 2.21 (1.40, 3.48), respectively. Their predominant roles were identified by the weighted quantile regression (WQS). Besides, restricted cubic spline analysis verified the relationship between molybdenum level and increased MRI risk in a linear and dose-response manner.

CONCLUSION

High levels of arsenic and molybdenum might be independent risk factors of MRI, and they showed combined effect. Our findings might provide vigorous evidence in preventing mild decline in renal function.

Urinary cadmium and peripheral blood telomere length predict the risk of renal function impairment: a study of 547 community residents of Shanxi, China

Few reports have investigated the predictive value of urinary cadmium (UCd) and telomere length on renal function impairment. Therefore, we constructed nomogram models, using a cross-sectional survey to analyze the potential function of UCd and telomere length in renal function impairment risk. We randomly selected two community populations in Shanxi, China, and general information of the subjects was collected through face-to-face questionnaire surveys. Venous blood of subjects was collected to detect absolute telomere length (ATL) by real-time quantitative chain reaction (RT-PCR). Collecting urinary samples detected UCd and urinary N-acetyl-β-d-glucosaminidase (UNAG). Estimated glomerular filtration rate (eGFR) was obtained based on serum creatinine (SCr). Nomogram models on risk prediction analysis of renal function impairment was constructed. After adjusting for other confounding factors, UCd (β = 0.853, 95% confidence interval (CI): 0.739 ~ 0.986) and ATL (β = 1.803, 95%CI: 1.017 ~ 1.154) were independent risk influencing factors for increased UNAG levels, and the risk factors for eGFR reduction were UCd (β = 1.011, 95%CI: 1.187 ~ 1.471), age (β = 1.630, 95%CI: 1.303 ~ 2.038), and sex (β = 0.181, 95%CI: 0.105 ~ 0.310). Using UCd, ATL, sex, and age to construct the nomogram, and the C-statistics 0.584 (95%CI: 0.536 ~ 0.632) and 0.816 (95%CI: 0.781 ~ 0.851) were obtained by internal verification of the calibration curve, C-statistics revealed nomogram model validation was good and using decision curve analysis (DCA) confirmed a good predictive value of the nomogram models. In a nomogram model, ATL, UCd, sex, and age were detected as independent risk factors for renal function impairment, with UCd being the strongest predictor.

Biomonitoring of urinary metals in athletes according to particulate matter air pollution before and after exercise

Exposure to air pollution during physical exercise is a health issue because fine particulate matter (dimension < 10 μm; PM₁₀) includes several inhalable toxic metals. Body metal changes in athletes according to air pollution are poorly known. Urinary concentrations of 15 metals: beryllium (Be⁹), aluminum (Al²⁷), vanadium (V⁵¹), chromium (Cr⁵¹ + Cr⁵²), manganese (Mn⁵⁵), cobalt (Co⁵⁹), nickel (Ni⁶¹), copper (Cu⁶³), zinc (Zn⁶¹), arsenic (As⁷⁵), selenium (Se⁸²), cadmium (Cd¹¹¹ + Cd¹¹²), thallium (Tl¹²⁵), lead (Pb²⁰⁷), and uranium (U²³⁸) were measured before and after ten 2-h training sessions in 8 non-professional Italian American-football players (18-28 years old, body mass index 24.2-33.6 kg/m²). Collectively, post-training sessions, urinary concentrations of As, Cd, Co, Cu, Mn, Ni, Pb, Se, Tl, and Zn were higher than pre-training sessions; Al, Be, Cr, and U did not change; conversely, V decreased. Subdividing training sessions according to air PM₁₀ levels: low (< 20 μg/m³), medium (20-40 μg/m³), and high (> 40 μg/m³), pre-session and post-session urinary concentrations of Be, Cd, Cu, and Tl were significantly higher (p < 0.05) in more polluted days, whereas V concentrations were lower (p < 0.001). All the remaining metals were unaffected. We first showed that PM₁₀ levels modulate urinary excretion of some toxic metals suggesting an effect of air pollution. The effects of toxic metals inhaled by athletes exercising in polluted air need further studies.