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Article

The NOAEL Equivalent of Environmental Cadmium Exposure Associated with GFR Reduction and Chronic Kidney Disease

by
Soisungwan Satarug
1,*,
Aleksandra Buha Đorđević
2,
Supabhorn Yimthiang
3,
David A. Vesey
1,4 and
Glenda C. Gobe
1,5,6
1
Kidney Disease Research Collaborative, Translational Research Institute, Brisbane 4102, Australia
2
Department of Toxicology “Akademik Danilo Soldatović”, University of Belgrade-Faculty of Pharmacy, 11000 Belgrade, Serbia
3
Occupational Health and Safety, School of Public Health, Walailak University, Nakhon Si Thammarat 80160, Thailand
4
Department of Nephrology, Princess Alexandra Hospital, Brisbane 4102, Australia
5
School of Biomedical Sciences, The University of Queensland, Brisbane 4072, Australia
6
NHMRC Centre of Research Excellence for CKD QLD, UQ Health Sciences, Royal Brisbane and Women’s Hospital, Brisbane 4029, Australia
*
Author to whom correspondence should be addressed.
Toxics 2022, 10(10), 614; https://doi.org/10.3390/toxics10100614
Submission received: 22 September 2022 / Revised: 12 October 2022 / Accepted: 14 October 2022 / Published: 15 October 2022
(This article belongs to the Special Issue Environmental Exposure to Toxic Chemicals and Human Health)
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Abstract

:
Cadmium (Cd) is a highly toxic metal pollutant present in virtually all food types. Health guidance values were established to safeguard against excessive dietary Cd exposure. The derivation of such health guidance figures has been shifted from the no-observed-adverse-effect level (NOAEL) to the lower 95% confidence bound of the benchmark dose (BMD), termed BMDL. Here, we used the PROAST software to calculate the BMDL figures for Cd excretion (ECd) associated with a reduction in the estimated glomerular filtration rate (eGFR), and an increased prevalence of chronic kidney disease (CKD), defined as eGFR ≤ 60 mL/min/1.73 m2. Data were from 1189 Thai subjects (493 males and 696 females) mean age of 43.2 years. The overall percentages of smokers, hypertension and CKD were 33.6%, 29.4% and 6.2%, respectively. The overall mean ECd normalized to the excretion of creatinine (Ecr) as ECd/Ecr was 0.64 µg/g creatinine. ECd/Ecr, age and body mass index (BMI) were independently associated with increased prevalence odds ratios (POR) for CKD. BMI figures ≥24 kg/m2 were associated with an increase in POR for CKD by 2.81-fold (p = 0.028). ECd/Ecr values of 0.38–2.49 µg/g creatinine were associated with an increase in POR for CKD risk by 6.2-fold (p = 0.001). The NOAEL equivalent figures of ECd/Ecr based on eGFR reduction in males, females and all subjects were 0.839, 0.849 and 0.828 µg/g creatinine, respectively. The BMDL/BMDU values of ECd/Ecr associated with a 10% increase in CKD prevalence were 2.77/5.06 µg/g creatinine. These data indicate that Cd-induced eGFR reduction occurs at relatively low body burdens and that the population health risk associated with ECd/Ecr of 2.77–5.06 µg/g creatinine was not negligible.

1. Introduction

Environmental exposure to cadmium (Cd) is inevitable for most people because the metal is present in almost all food types [1,2,3]. The realization in the 1940s that the condition referred to as “itai-itai” disease was due to the consumption of rice heavily contaminated with Cd brought into focus the real threat to health posed by this metal [4,5]. Itai-itai disease is the most severe form of human Cd poisoning, characterized by severe damage to the kidneys and bones, resulting in multiple bone fractures due to osteoporosis and osteomalacia [4,5]. The pathologic symptoms of the itai-itai disease have been replicated in Cd-treated cynomolgus monkeys [6].
To safeguard against excessive dietary Cd exposure, health guidance such as a tolerable intake level of Cd was established [7]. The Joint FAO/WHO Expert Committee on Food Additives and Contaminants (JECFA) considered the kidney to be the critical target of Cd toxicity [8]. By definition, the provisional tolerable weekly intake (PTWI) for a chemical with no known biological function is an estimate of the amount that can be ingested weekly over a lifetime without appreciable health risk. Subsequently, the PTWI for Cd was amended to a tolerable monthly intake (TMI) of 25 μg per kg body weight per month, equivalent to 0.83 μg per kg body weight per day [8]. This tolerable intake level for Cd was derived from a risk assessment model that assumed an increase in excretion of β2-microglobulin (β2M) (Eβ2M) above 300 μg/g creatinine as the point of departure (POD) [8]. However, we have shown that such an increase in Eβ2M reflected tubular dysfunction and nephron loss, evident from a reduction in estimated glomerular filtration rate (eGFR) to 60 mL/min/1.73 m2 or below [9,10]. In effect, a tolerable intake level of Cd derived from the Eβ2M-based POD is not sufficiently low to be without an impact on human health.
Current evidence suggests that sufficient tubular injury disables glomerular filtration and leads to nephron atrophy and a decrease in GFR [11,12,13]. Accordingly, we argue that a reduction in eGFR due to Cd nephropathy could serve as the POD from which health guidance values should be derived. Owing to some shortcomings of the no-observed-adverse-effect level (NOAEL), the benchmark dose (BMD) has been used as the POD [7,14,15,16]. The BMD is a dose level, derived from an estimated dose–response curve, associated with a specified change in response, termed benchmark response (BMR) which can be set at 1%, 5%, or 10% as required [14,15,16].
The present study had two major aims. The first aim was to characterize a reduction in eGFR and risk factors of chronic kidney disease (CKD) in a sufficiently large group of people with a wide range of environmental Cd exposure. The risk factors considered included age, body mass index (BMI), smoking, hypertension, and Cd exposure measured as excretion of Cd (ECd). The second aim was to compute the lower 95% confidence bound of BMD (BMDL) and the BMD upper confidence limit (BMDU) of ECd associated with eGFR reduction and an increase in the prevalence of CKD.

2. Materials and Methods

2.1. Participants

To represent a large group of subjects with a wide range of environmental Cd exposure levels suitable for the dose–response analysis and health risk calculation, we assembled archived data from 1189 persons who participated in large population-based studies undertaken in a Cd contamination area in the Mae Sot District, Tak Province (n = 537), and low exposure locations in Bangkok and Nakhon–Si–Thammarat Province (n = 652). The Institutional Ethical Committees of Chulalongkorn University, Chiang Mai University and the Mae Sot Hospital approved the study protocol for the Mae Sot and Bangkok groups. The Office of the Human Research Ethics Committee of Walailak University in Thailand approved the study protocol for the Nakhon Si Thammarat group [17,18].
All participants gave informed consent prior to participation. They had lived at their current addresses for at least 30 years. Exclusion criteria were pregnancy, breastfeeding, a history of metalwork, and a hospital record or physician’s diagnosis of advanced chronic disease. Because occupational exposure was an exclusion criterion, we presumed that all participants had acquired Cd from the environment. Diabetes was defined as fasting plasma glucose levels ≥ 126 mg/dL or a physician’s prescription of anti-diabetic medications. Hypertension was defined as systolic blood pressure ≥ 140 mmHg, diastolic blood pressure ≥ 90 mmHg, a physician’s diagnosis, or prescription of anti-hypertensive medications.

2.2. Collection and Analysis of Biological Specimens

Simultaneous blood and urine sampling are required to normalize ECd, to Ccr. Accordingly, second-morning urine samples were collected after an overnight fast, and whole blood samples were obtained within 3 hours after the urine sampling. Aliquots of urine, whole blood and plasma were stored at −20 °C or −80 °C for later analysis. The assay for urine and plasma concentrations of creatinine ([cr]u and [cr]p) was based on the Jaffe reaction.
For the Bangkok group, urine concentration of Cd ([Cd]u) was determined by inductively-coupled plasma mass spectrometry (ICP/MS, Agilent 7500, Agilent Technologies, Santa Clara, CA, USA). Multi-element standards (EM Science, EM Industries, Inc., Newark, NJ, USA) were used to calibrate the Cd analyses. Quality assurance and control were conducted with simultaneous analyses of samples of the reference urine Lyphochek® (Bio-Rad, Gladesville, New South Wales, Australia), which contained low- and high-range Cd levels. A coefficient of variation value of 2.5% was obtained for Cd in the reference urine. The low limit of detection (LOD) of urine Cd was 0.05 µg/L. The urine samples containing Cd below the LOD were assigned as the LOD divided by the square root of 2 [19].
For the Nakhon–Si–Thammarat group, [Cd]u was determined with the GBC System 5000 Graphite Furnace Atomic Absorption Spectrophotometer (AAS) (GBC Scientific Equipment, Hampshire, IL, USA). Instrumental metal analysis was calibrated with multi-element standards (Merck KGaA, Darmstadt, Germany). Reference urine metal control levels 1, 2, and 3 (Lyphocheck, Bio-Rad, Hercules, CA, USA) were used for quality control, analytical accuracy, and precision assurance. The analytical accuracy of metal detection was checked by an external quality assessment every 3 years. The LOD of urine Cd was 0.1 µg/L. When [Cd]u was below its detection limit, the Cd concentration assigned was the detection limit divided by the square root of 2 [19].
For the Mae Sot group, [Cd]u was determined with AAS (Shimadzu Model AA-6300, Kyoto, Japan). Urine standard reference material No. 2670 (National Institute of Standards, Washington, DC, USA) was used for quality assurance and control purposes. The LOD of Cd quantitation, defined as 3 times the standard deviation of blank measurements was 0.06 µg/L. None of the urine samples from this group contained [Cd]u below the detection limit.

2.3. Estimated Glomerular Filtration Rates (eGFR)

The GFR is the product of nephron number and mean single nephron GFR, and in theory, the GFR is indicative of nephron function [20,21,22]. In practice, the GFR is estimated from established chronic kidney disease-epidemiology collaboration (CKD-EPI) equations and is reported as eGFR [21].
Male eGFR = 141 × [plasma creatinine/0.9]Y × 0.993age, where Y = −0.411 if [cr]p ≤ 0.9 mg/dL, Y = −1.209 if [cr]p > 0.9 mg/dL. Female eGFR = 144 × [plasma creatinine/0.7]Y × 0.993age, where Y = −0.329 if [cr]p ≤ 0.7 mg/dL, Y = −1.209 if [cr]p > 0.7 mg/dL. For dichotomous comparisons, CKD was defined as eGFR ≤ 60 mL/min/1.73 m2. CKD stages 1, 2, 3a, 3b, 4, and 5 corresponded to eGFR of 90–119, 60–89, 45–59, 30–44, 15–29, and <15 mL/min/1.73 m2, respectively.

2.4. Normalization of ECd to Ecr and Ccr

Ex was normalized to Ecr as [x]u/[cr]u, where x = Cd; [x]u = urine concentration of x (mass/volume); and [cr]u = urine creatinine concentration (mg/dL). The ratio [x]u/[cr]u was expressed in μg/g of creatinine.
Ex was normalized to Ccr as Ex/Ccr = [x]u[cr]p/[cr]u, where x = Cd; [x]u = urine concentration of x (mass/volume); [cr]p = plasma creatinine concentration (mg/dL); and [cr]u = urine creatinine concentration (mg/dL). Ex/Ccr was expressed as the excretion of x per volume of filtrate [23].

2.5. Benchmark Dose Computation and Benchmark Dose–Response (BMR) Setting

We used the web-based PROAST software version 70.1 (https://proastweb.rivm.nl accessed on 13 October 2022) to compute the BMD figures for ECd/Ecr and ECd/Ccr associated with glomerular dysfunction. A specific effect size termed the benchmark response (BMR) was set at 5% for a continuous eGFR reduction endpoint and at 10% for a quantal endpoint where eGFR ≤ 60 mL/min/1.73 m2. For a continuous endpoint, BMD values were computed from fitting datasets to four dose–response models, including inverse exponential, natural logarithmic, exponential, and Hill models. For a quantal endpoint, BMD values were calculated from fitting datasets to seven dose–response models that included two-stage, logarithmic logistic, Weibull, logarithmic probability, gamma, exponential and Hill models. The BMD 95% confidence intervals of ECd/Ecr and ECd/Ccr were from model averaging using bootstrap with 200 repeats.
The BMDL and BMDU corresponded to the lower bound and upper bound of the 95% confidence interval (CI) of BMD. The wider the BMDL-BMDU difference, the higher the statistical uncertainty in the dataset [23,24,25,26]. BMDL/BMDU figures of ECd for the glomerular endpoint were calculated for males, females and all subjects.

2.6. Statistical Analysis

Data were analyzed with IBM SPSS Statistics 21 (IBM Inc., New York, NY, USA). The one-sample Kolmogorov–Smirnov test was used to identify departures of continuous variables from a normal distribution, and a logarithmic transformation was applied to variables that showed rightward skewing before they were subjected to parametric statistical analysis. The Mann–Whitney U-test was used to compare mean differences between the two groups. The Chi-square test was used to determine differences in percentage and prevalence data. The multivariable logistic regression analysis was used to determine the Prevalence Odds Ratio (POR) for CKD in relation to six independent variables; age, BMI, gender, smoking, hypertension and Cd exposure measures as ECd. We employed two models in each logistic regression analysis: model 1 incorporated log2(ECd/Ecr) or three ECd/Ecr groups; model 2 incorporated log2(ECd/Ccr) or three ECd/Ccr groups. All other independent variables in models 1 and 2 were identical. For all tests, p-values ≤ 0.05 for two-tailed tests were assumed to indicate statistical significance.

3. Results

3.1. Characterization of Cadmium Exposure by Sex and Smoking

Table 1 provides demographic data of participants (493 males and 696 females) stratified by sex and smoking status.
The overall mean age of participants was 43.2 years, and the overall percentages of current smokers plus those who had stopped smoking for less than 10 years, hypertension and low eGFR were 33.6%, 29.4% and 6.2%, respectively. The overall mean [Cd]u and mean ECd/Ecr were 0.94 µg/L and 0.64 µg/g creatinine, while the overall mean ECd/Ccr × 100 was 1.02 µg/L filtrate.
Smoking was higher among males (57.4%) than females (16.4%). In both sexes, % of smokers and non-smokers with hypertension did not differ. However, % of low eGFR among smokers was 3.7- and 3.8-fold higher than non-smokers in female and male groups, respectively. For the female group only, the mean BMI was 6 % lower in smokers than non-smokers (p = 0.004).
For the male group, the mean [Cd]u in smokers was 5.4-fold higher than nonsmokers (1.73 vs. 0.32 µg/L, p < 0.001). Mean ECd/Ecr and mean ECd/Ccr in smokers were 2.9- and 4.1-fold higher than in nonsmokers, respectively.
For the female group, the mean [Cd]u in smokers was 6.4-fold higher than nonsmokers (4.84 vs. 0.75 µg/L, p < 0.001). Mean ECd/Ecr and mean ECd/Ccr in smokers were 3.2-and 6-fold higher than in nonsmokers, respectively.

3.2. Characterization of CKD Risk factors

Table 2 provides the results of a logistic regression analysis where ECd/Ecr and ECd/Ccr were continuous variables, while age and BMI were categorical variables.
An independent effect on the POR for CKD was observed for ECd/Ecr, BMI and age (Table 2). Sex, smoking and hypertension were not associated with the POR for CKD. Doubling of ECd/Ecr was associated with an increase in POR for CKD by 1.47-fold (p < 0.001). BMI figures ≥ 24 kg/m2 were associated with 2.81-fold increase in POR for CKD (p = 0.028). Compared with those aged 16–45 years, the POR values for CKD were 14-, 28- and 141-fold higher in those aged 46–55, 56–65, and 66–87 years, respectively.
In an equivalent analysis of the Ccr-normalized datasets, ECd/Ccr, BMI and age were independently associated with increased POR for CKD. Sex, smoking and hypertension were not associated with the POR for CKD. Doubling of ECd/Ccr was associated with an increase in POR for CKD by 1.96-fold (p < 0.001). BMI figures ≥ 24 kg/m2 were associated with a 3.12-fold increase in POR for CKD (p = 0.022). Compared with those aged 16–45 years, the POR values for CKD were 10-, 35- and 199-fold higher in those aged 46–55, 56–65, and 66–87 years, respectively.

3.3. Cadmium Excretion in Relation to the Risk of CKD

Table 3 provides the results of a logistic regression analysis where age and BMI were continuous variables, while ECd/Ecr was a categorical variable in model 1, and ECd/Ccr was categorical in model 2.
Age and BMI were independently associated with increased POR for CKD in both models 1 and 2. Compared with ECd/Ecr ≤ 0.37 µg/g creatinine (model 1), the POR for CKD was increased by 6.2- and 10.6-fold in those with ECd/Ecr values of 0.38–2.49 and ≥2.5 µg/g creatinine, respectively. Compared with ECd/Ccr ≤ 9.9 ng/L filtrates (model 2), the POR for CKD was increased by 4.4- and 20.8-fold in those with ECd/Ccr values of 10–49.9 and ≥50 ng/L filtrate, respectively.

3.4. BMDL/BMDU Figures of ECd Associated with Reduced Glomerular Function

3.4.1. Ecr-Normalized Dataset

As data in Figure 1 and Figure 2 indicate, the differences between BMDL and BMDU figures of ECd/Ecr were small for both continuous and quantal endpoints. The BMDL-BMDU figures of ECd/Ecr calculated from Cd-dose and eGFR response models were higher in females than males.
For all subjects, the BMDL/BMDU of ECd /Ecr for continuous and quantal endpoints were 0.828/1.71 and 2.77/5.06 µg/g creatinine, respectively.

3.4.2. Ccr-Normalized Dataset

As data in Figure 3 and Figure 4 indicate, the differences between BMDL and BMDU figures of ECd/Ccr were small for both continuous and quantal endpoints. The BMDL-BMDU figures of ECd/Ecr calculated by Cd-dose and eGFR response models in males and females were nearly identical.
For all subjects, the BMDL/BMDU of ECd /Ccr for continuous and quantal endpoints were 10.4/24 and 56.1/83.1 ng/L filtrate, respectively.

4. Discussion

In a dose–response analysis of a large dataset from apparently healthy participants (mean age 48.3 years), older age and higher BMI were independently associated with higher risks of CKD, based on the low eGFR criterion (Table 2). These findings are consistent with the literature reports of age, overweight and obesity as common CKD risk factors [27,28,29,30]. In addition to these two risk factors, we have found the measure of long-term exposure to Cd (ECd/Ecr) to be another independent risk factor of CKD (Table 3). An association between low environmental Cd exposure and a decrease in eGFR to levels commensurate with CKD has been observed in population-based studies in the U.S. [31,32,33,34], Taiwan [35] and Korea [36,37,38].
In this study, the risk of CKD was increased by 6.2- and 10.6-fold, when ECd/Ecr ≤ 0.37 µg/g creatinine rose to 0.38–2.49 and ≥ 2.5 µg/g creatinine, respectively. These Cd-dose dependent increases in the risk of CKD were strengthened by the results obtained from the Ccr-normalized dataset where the risk of CKD was increased by 4.4- and 20.8-fold, comparing ECd/Ccr ≤ 9.9 ng/L filtrates with ECd/Ccr of 10–49.9 and ≥50 ng/L filtrate, respectively. This confirmation is noteworthy because normalizing ECd to Ecr can cause a wide dispersion of dataset due to the interindividual differences in Ecr such as muscle mass which is unrelated to neither Cd exposure nor nephron function [11,12].
Because of such increased variance in datasets introduced by Ecr-normalization, the effect of chronic exposure to low-dose Cd on eGFR was not realized. For example, a systematic review and meta-analysis of pooled data from 28 studies reported that the risk of proteinuria was increased by 1.35-fold when comparing the highest vs. lowest category of Cd dose metrics, but an increase in the risk of low eGFR was statistically insignificant (p = 0.10) [39]. An erroneous conclusion that chronic Cd exposure was not associated with a progressive eGFR reduction was also made in another systematic review [40].
A significant relationship was seen between ECd and a decrease in eGFR with adjustment for covariates (Table 3). We subsequently applied the BMD method to our Ecr- and Ccr-normalized datasets to identify ECd/Ecr and ECd/Ccr values below which an adverse effect of Cd on eGFR can be discerned. The BMDL/BMDU figures of ECd/Ecr, estimated from the eGFR reduction endpoint were 0.839/1.81, 0.849/1.74 and 0.828/1.71 µg/g creatinine in males, females and all subjects, respectively (Figure 1). The corresponding BMDL/BMDU figures of ECd/Ccr were 11.3/24.3, 11.3/24.1 and 10.4/24 ng/L filtrate in males, females and all subjects, respectively (Figure 3).
The BMD values of Cd exposure levels calculated from toxic tubular cell injury and reduced tubular reabsorption of the filtered protein β2M can be found in numerous studies [41,42]. In contrast, a report of BMDL/BMDU of Cd exposure levels associated with eGFR reduction could only be found in a study of 790 Swedish women, aged 53–64 years, where the reported BMDL values for the glomerular endpoint were 0.7–1.2 μg/g creatinine [43]. These BMD values were slightly lower than those calculated for females in the present study (0.849/1.74 μg/g creatinine). The differences may be attributable to lower Ecr in Thai women than in Swedish women. Nevertheless, all these BMD values were lower than ECd/Ecr of 5.24 µg/g creatinine, which suggested to be a threshold level for the nephrotoxicity of Cd when Eβ2M/Ecr > 300 was used as the POD [8].
In our quantal eGFR endpoint analysis (Figure 2), the BMDL/BMDU values of ECd associated with a 10% increase in CKD prevalence were 2.77/5.06 µg/g creatinine (56.1/83.1 ng/L filtrate). These data suggested that population CKD prevalence was likely to be smaller than 10% at ECd/Ecr < 2.77 µg/g creatinine (<56.1 ng/L filtrates). Thus, the population health risk associated with ECd/Ecr < 2.77 µg/g creatinine could not be discerned. The impact of Cd exposure on GFR has long been underestimated due to the common practice of normalizing ECd to Ecr. The comparability of guidelines between populations could be improved by the universal acceptance of a consistent normalization of ECd to Ccr that eliminates the effect of muscle mass on Ecr, thereby giving a more accurate assessment of the severity of Cd nephropathy [10].
A tolerable intake level of 0.28 μg/kg body weight per day was derived in a risk calculation using pooled data from Chinese population studies [44]. This consumption level, equivalent to 16.8 µg/day for a 60 kg person, was derived from an Eβ2M/Ecr endpoint where the BMDL value of ECd/Ecr for such an endpoint was 3.07 μg/g creatinine. This BMDL estimate was 3.7-fold higher than the BMDL of 0.828 µg/g creatinine derived in the present study. In another Chinese population study, dietary Cd intake estimates at 23.2, 29.6, and 36.9 μg/d were associated with 1.73-, 2.93- and 4.05-fold increments in the prevalence of CKD, compared with the 16.7 μg/d intake level [45]. A diet high in rice, pork, and vegetables was associated with a 4.56-fold increase in the prevalence of CKD [45].
The European Food Safety Authority (EFSA) also used the β2M endpoint. However, the EFSA included an uncertainty factor (safety margin), and an intake of 0.36 μg/kg body weight per day for 50 years as an acceptable Cd ingestion level or a reference dose (RfD) [46]. The EFSA designated ECd/Ecr of 1 μg/g creatinine as the toxicity threshold level for an adverse effect on kidneys. This Cd excretion of 1 μg/g creatinine is 17 % higher than our NOAEL equivalent of Cd excretion of 0.828 µg/g creatinine.
The Cd toxicity threshold level, RfD and an acceptable consumption level derived from the β2M excretion above ≥300 µg/ g creatinine do not appear to be without an appreciable health risk. In theory, health-risk assessment should be based on the most sensitive endpoint with consideration given to subpopulations with increased susceptibility to Cd toxicity such as children.
In the present study, the body burden of Cd, measured as ECd/Ecr, was increased by 3-fold in men and women who smoked cigarettes (Table 1). These results are expected, given that the tobacco plant accumulates high levels of Cd in its leaves, and the volatile metallic Cd and oxide (CdO) generated from cigarette burning are more bioavailable than Cd that enters the body through the gut [47,48].
The diet is the main Cd exposure source for non-smoking and non-occupationally-exposed populations. In a temporal trend analysis of environmental Cd exposure in the U.S., the mean urinary Cd fell by 29% in men (0.58 vs. 0.41 μg/g creatinine, p < 0.001) over 18 years (NHANES 1988–2006), but not in women (0.71 vs. 0.63 μg/g creatinine, p = 0.66) [49]. Such a reduction in Cd exposure among men was attributable to a decrease in smoking prevalence [50]. In contrast, total diet studies in Australia [51], France [52], Spain [53] and the Netherlands [2] reported that dietary Cd exposure levels among young children exceeded the current health guidance values. These data are concerning for the reasons below.
CKD is a progressive syndrome with high morbidity and mortality and affects 8% to 16% of the world’s population [27,28,29,30]. An upward trend of its incidence continues, while an adverse effect of Cd on eGFR and the risk of CKD have increasingly been reported. Higher Cd excretion was associated with lower eGFR in studies from Guatemala [54] and Myanmar [55]. The effect of Cd exposure on eGFR observed in children is particularly concerning. In a prospective cohort study of Bangladeshi preschool children, an inverse relationship between urinary Cd excretion and kidney volume was seen in children at 5 years of age. This was in addition to a decrease in eGFR [56]. Urinary Cd levels were inversely associated with eGFR, especially in girls. In another prospective cohort study of Mexican children, the reported mean for Cd intake at the baseline was 4.4 µg/d, which rose to 8.1 µg/d after nine years, when such Cd intake levels showed a marginally inverse association with eGFR [57].

5. Conclusions

Environmental exposure to Cd, old age, and elevated BMI are independent risk factors for reduced eGFR. For the first time, the BMDL/BMDU figures of Cd excretion levels associated with a decrease in eGFR have been computed for men and women. The narrow BMDL-BMDU differences indicate the high degree of statistical certainty in these derived NOAEL equivalent figures. The BMDL/BMDU estimates of the Cd excretion associated with a decrease in eGFR in all subjects are 0.828/1.71 µg/g creatinine. The BMDL/BMDU estimates of Cd excretion associated with a 10% increase in the prevalence of CKD are 2.77/5.06 µg/g creatinine. These NOAEL equivalents indicate a decrease in eGFR due to Cd nephropathy occurs at the body burdens lower than those associated with Cd excretion of 5.24 µg/g creatinine and an increase in β2M excretion above 300 µg/g creatinine. The established nephrotoxicity threshold level for Cd is outdated and is not protective of human health. Human health risk assessment should be based on current scientific research data.

Author Contributions

Conceptualization, S.S.; methodology, S.S., S.Y. and A.B.Đ.; formal analysis, S.S. and A.B.Đ.; investigation, S.S. and S.Y.; resources, G.C.G. and D.A.V.; writing—original draft preparation, S.S.; writing—review and editing, G.C.G. and D.A.V.; project administration, S.S. and S.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This study analyzed archived data taken from published reports [17,18]. Ethical review and approval were not applicable.

Informed Consent Statement

All participants took part in the study after giving informed consent.

Data Availability Statement

All data are contained within this article.

Acknowledgments

This work was supported with resources from the Kidney Disease Research Collaborative, Translational Research Institute and the Department of Nephrology, Princess Alexandra Hospital. It was also supported by the resources of the Department of Toxicology “Akademik Danilo Soldatović”, University of Belgrade-Faculty of Pharmacy, Serbia.

Conflicts of Interest

The authors have declared no potential conflict of interest.

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Figure 1. BMD estimates of ECd/Ecr from eGFR reduction endpoint with BMR at 5%. ECd/Ecr and eGFR data were fitted to an inverse exponential model (a), a natural logarithmic model (b), an exponential model (c), and Hill model (d). Bootstrap curves were based on model averaging of ECd/Ecr BMD estimates for all subjects (e). Outputs of all fitted models as BMDL and BMDU estimates of ECd/Ecr associated with a 5 % reduction in eGFR (f).
Figure 1. BMD estimates of ECd/Ecr from eGFR reduction endpoint with BMR at 5%. ECd/Ecr and eGFR data were fitted to an inverse exponential model (a), a natural logarithmic model (b), an exponential model (c), and Hill model (d). Bootstrap curves were based on model averaging of ECd/Ecr BMD estimates for all subjects (e). Outputs of all fitted models as BMDL and BMDU estimates of ECd/Ecr associated with a 5 % reduction in eGFR (f).
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Figure 2. BMD estimates of ECd/Ecr from quantal eGFR endpoint with BMR at 10%. Bootstrap curves were based on model averaging 95% confidence intervals of BMD of ECd/Ecr in males and females (a) and in all subjects (b). Outputs of all fitted models as BMDL and BMDU estimates of ECd/Ecr associated with a 10% increase in prevalence of CKD (c).
Figure 2. BMD estimates of ECd/Ecr from quantal eGFR endpoint with BMR at 10%. Bootstrap curves were based on model averaging 95% confidence intervals of BMD of ECd/Ecr in males and females (a) and in all subjects (b). Outputs of all fitted models as BMDL and BMDU estimates of ECd/Ecr associated with a 10% increase in prevalence of CKD (c).
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Figure 3. BMD estimates of ECd/Ccr from eGFR reduction endpoint with BMR at 5%. ECd/Ccr and eGFR data were fitted to an inverse exponential model (a), a natural logarithmic model (b), an exponential model (c), and Hill model (d). Bootstrap curves were based on model averaging of ECd/Ccr BMD estimates for all subjects (e). Outputs of all fitted models as BMDL and BMDU estimates of ECd/Ccr associated with a 5% reduction in eGFR (f).
Figure 3. BMD estimates of ECd/Ccr from eGFR reduction endpoint with BMR at 5%. ECd/Ccr and eGFR data were fitted to an inverse exponential model (a), a natural logarithmic model (b), an exponential model (c), and Hill model (d). Bootstrap curves were based on model averaging of ECd/Ccr BMD estimates for all subjects (e). Outputs of all fitted models as BMDL and BMDU estimates of ECd/Ccr associated with a 5% reduction in eGFR (f).
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Figure 4. BMD estimates of ECd/Ccr from quantal eGFR endpoint with BMR at 10%. Bootstrap curves were based on model averaging 95% confidence intervals of BMD of ECd/Ccr in males and females (a) and in all subjects (b). Outputs of all fitted models as BMDL and BMDU estimates of ECd/Ecr associated with a 10% increase in the prevalence of CKD (c).
Figure 4. BMD estimates of ECd/Ccr from quantal eGFR endpoint with BMR at 10%. Bootstrap curves were based on model averaging 95% confidence intervals of BMD of ECd/Ccr in males and females (a) and in all subjects (b). Outputs of all fitted models as BMDL and BMDU estimates of ECd/Ecr associated with a 10% increase in the prevalence of CKD (c).
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Table
Table 1. Characteristics of participants stratified by sex and smoking status.
Table 1. Characteristics of participants stratified by sex and smoking status.
Parameters All subjects
n 1189 (33.6%
Smokers)		Males, n 493 (57.4% Smokers)Females, n 696 (16.8% Smokers)
Nonsmokers
n 210		Smokers
n 283		Nonsmokers
n 579		Smokers
n 117
Age, years43.2 ± 14.035.9 ± 13.045.0 ± 14.8 ***42.6 ± 12.954.2 ± 10.1 ###
Hypertension (%)29.426.527.230.833.3
BMI, kg/m223.0 ± 3.922.4 ± 3.022.3 ± 3.423.8 ± 4.022.4 ± 4.6 #
BMI groups (%)
12–1810.59.212.2 *7.421.4
19–2347.156.957.2 **41.636.8 ###
≥2442.434.030.651.041.9 ###
eGFR a, mL/min/1.73 m293.7 ± 2096.6 ± 17.691.9 ± 22.195.9 ± 19.381.8 ± 22.0 ###
eGFR ≤ 60 mL/min/1.73 m2 (%)6.22.48.8 **4.316.2 ###
eGFR, mL/min/1.73 m2 (%) b
>1207.89.05.79.71.7 ###
90–12053.861.056.554.133.3 ###
60–8932.827.629.7 *32.849.6 ###
30–595.01.97.1 **3.313.7
15–29 0.60.51.10.21.7
Plasma creatinine, mg/dL0.88 ± 0.241.00 ± 0.211.00 ± 0.270.76 ± 0.160.82 ± 0.27 ##
Urine creatinine, mg/dL104.4 ± 73.581.1 ± 78107.0 ± 75.6 ***67.9 ± 68.979.8 ± 64.8
Urine Cd, µg/L0.94 ± 9.690.32 ± 5.961.73 ± 15.9 ***0.75 ± 6.464.84 ± 6.38 ###
Normalized to Ecr as Ex/Ecr c
ECd/Ecr, µg/g creatinine0.64 ± 6.120.32 ± 3.290.94 ± 8.85 ***0.57 ± 4.621.83 ± 7.27 ###
Normalized to Ccr as Ex/Ccr d
ECd/Ccr × 100, µg/L filtrate1.02 ± 8.190.39 ± 4.751.61 ± 12.61 ***0.83 ± 5.275.00 ± 9.36 ###
n, number of subjects; BMI, body mass index; eGFR, estimated glomerular filtration rate; Ex, excretion of x; cr, creatinine; Ccr, clearance of creatinine. a eGFR determined with Chronic Kidney Disease Epidemiology Collaboration (CKD–EPI) equations [20]; b eGFR of 90–119, 60–89, 45–59, 30–44, 15–29, and <15 mL/min/1.73 m2 corresponded to CKD stages 1, 2, 3a, 3b, 4, and 5, respectively. c Ex/Ecr = [x]u/[cr]u; d Ex/Ccr = [x]u[cr]p/[cr]u, where x = Cd [23]. Data for age, eGFR and BMI are arithmetic means ± standard deviation (SD). Data for all other continuous variables are geometric means ± SD. Data for BMI are from 951 subjects; data for hypertension are from 917 subjects; data for all other variables are from 1189 subjects. For each test, p ≤ 0.05 identifies statistical significance, determined by Chi-Square test and Mann–Whitney U test for % differences and mean differences, respectively. Compared with non-smoking males * p = 0.029–0.042, ** p = 0.001–0.006, *** p ≤ 0.001. Compared with non-smoking females, # p = 0.004, ## p = 0.001, ### p ≤ 0.001.
Table
Table 2. Increment in risk of chronic kidney disease in relation to age, BMI and cadmium exposure.
Table 2. Increment in risk of chronic kidney disease in relation to age, BMI and cadmium exposure.
Independent Variables/
Factors		Number of
Subjects 		a CKD
β CoefficientsPOR95% CIp
(SE) LowerUpper
Model 1
Log2[(ECd/Ecr) × 103], µg/g creatinine9170.385 (0.072)1.4701.2761.692<0.001
Hypertension2760.490 (0.312)1.6320.8853.0080.117
Gender (female)5620.028 (0.340)1.0290.5282.0020.934
Smoking3350.209 (0.337)1.2320.6372.3830.536
BMI, kg/m2
12–1899Referent
19–234310.057 (0.426)1.0580.4592.4390.894
≥243871.033 (0/470)2.8101.1187.0640.028
Age, years
16–45392Referent
46–553482.655 (1.036)14.231.867108.40.010
56–651003.340 (1.059)28.213.538224.90.002
66–87774.950 (1.055)141.217.871116<0.001
Model 2
Log2[(ECd/Ccr) × 105], µg/L filtrate9170.674 (0.107)1.9621.5892.422<0.001
Hypertension2760.551 (0.326)1.7350.9163.2870.091
Gender (female)562−0.174 (0.366)0.8400.4101.7190.633
Smoking335−0.058 (0.351)0.9440.4741.8790.869
BMI, kg/m2
12–1899Referent
19–234310.103 (0.457)1.1090.4522.7170.822
≥243871.147 (0.500)3.1501.1818.4000.022
Age, years
16–45392Referent
46–553482.298 (1.036)9.9511.30575.880.027
56–651003.543 (1.062)34.574.312277.20.001
66–87775.292 (1.066)198.624.591605<0.001
POR, Prevalence Odds Ratio; S.E., standard error of mean; CI, confidence interval. a CKD was defined as estimated glomerular filtration rate (eGFR) ≤ 60 mL/min/1.73 m2. Coding; female = 1, male = 2, hypertensive = 1, normotensive = 2, smoker = 1, non-smoker = 2. Data were generated from logistic regression analyses relating POR for CKD to six independent variables, listed in the first column. For all tests, p-values < 0.05 indicate statistical significance. Log2[(ECd/Ecr) × 103] was incorporated into model 1; log2[(ECd/Ccr) × 105] was incorporated into model 2. Other independent variables in models 1 and 2 were identical. β coefficients indicate an effect size of each independent variable on POR for CKD.
Table
Table 3. Dose–response relationship between cadmium excretion and the risk of chronic kidney disease.
Table 3. Dose–response relationship between cadmium excretion and the risk of chronic kidney disease.
Independent Variables/
Factors		Number of
Subjects 		a CKD
β CoefficientsPOR95% CIp
(SE) LowerUpper
Model 1
Age, years9170.126 (0.016)1.1351.1001.170<0.001
BMI, kg/m29170.082 (0.038)1.0861.0091.1690.028
Gender (female)5620.124 (0.337)1.1320.5852.1900.713
Hypertension2760.304 (0.310)1.3550.7382.4860.327
Smoking3350.173 (0.345)1.1890.6052.3380.615
ECd/Ecr, µg/g creatinine
≤0.37358Referent
0.38–2.493331.819 (0.565)6.1642.03518.670.001
≥2.52262.362 (0.557)10.613.56231.60<0.001
Model 2
Age, years9170.141 (0.016)1.1521.1161.189<0.001
BMI, kg/m29170.099 (0.039)1.1041.0231.1910.011
Gender (female)5620.191 (0.356)1.211.6022.4340.591
Hypertension2760.240 (0.314)1.2710.6872.3530.445
Smoking335−0.033 (0.359)0.9680.4791.9560.927
ECd/Ccr, ng/L filtrate
≤9.9346Referent
10–49.93261.470 (0.642)4.3501.23715.300.022
≥502453.036 (0.637)20.825.97972.52<0.001
POR, Prevalence Odds Ratio; S.E., standard error of mean; CI, confidence interval. a CKD was defined as estimated glomerular filtration rate (eGFR) ≤ 60 mL/min/1.73 m2. Coding; female = 1, male = 2, hypertensive = 1, normotensive = 2, smoker = 1, non-smoker = 2. Data were generated from logistic regression analyses relating POR for CKD to six independent variables listed in the first column. For all tests, p-values < 0.05 indicate statistical significance. Three ECd/Ecr categories were incorporated into model 1; three ECd/Ccr × 100 categories were incorporated into model 2. Other independent variables in models 1 and 2 were identical. β coefficients indicate an effect size of each independent variable on POR for CKD.
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Satarug, S.; Đorđević, A.B.; Yimthiang, S.; Vesey, D.A.; Gobe, G.C. The NOAEL Equivalent of Environmental Cadmium Exposure Associated with GFR Reduction and Chronic Kidney Disease. Toxics 2022, 10, 614. https://doi.org/10.3390/toxics10100614

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Satarug S, Đorđević AB, Yimthiang S, Vesey DA, Gobe GC. The NOAEL Equivalent of Environmental Cadmium Exposure Associated with GFR Reduction and Chronic Kidney Disease. Toxics. 2022; 10(10):614. https://doi.org/10.3390/toxics10100614

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Satarug, Soisungwan, Aleksandra Buha Đorđević, Supabhorn Yimthiang, David A. Vesey, and Glenda C. Gobe. 2022. "The NOAEL Equivalent of Environmental Cadmium Exposure Associated with GFR Reduction and Chronic Kidney Disease" Toxics 10, no. 10: 614. https://doi.org/10.3390/toxics10100614

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