Characteristics of the study population
In our study, we included 58,864 outpatients. Most of them had no known kidney disease nor heavy metal exposure. There were 22,267 (37.8%) men, 36,569 (62.1%) women, and 28 (< 0.01%) patients with unknown sex. The average age was 50.78 years. Data was available for 25,547 outpatients on arsenic levels (median: 0.8 µg/L), 52,082 outpatients on lead levels (median 13.6 µg/L), and 52,961 outpatients on mercury levels (median: 0.8 µg/L) (Table 1; Fig. 1). The detection limits of the ICP-MS system were sufficiently sensitive to identify traces of arsenic, lead, and mercury in whole blood samples. The lower limits of quantification (LLOQ) for our assays were as follows: arsenic: 0.2 µg/L (7.2% of samples in the current study); lead: 2 µg/L (0.1% of samples in the current study); mercury: 0.2 µg/L (12.5% of samples in the current study). The median (IQR) eGFR level was 92.14 (79.44-103.85) mL/min/1.73m2 (Fig. 2).
Distribution of the three metals (arsenic, lead, and mercury).
Distribution of heavy metals (arsenic, lead, mercury) in different age and sex subgroups
Figure 1 displays, for arsenic, lead, and mercury, that as their whole blood concentration increases, the frequency mostly decreases. Comparing age subgroups (≤ 20, 20s, 30s, 40s, 50s, 60s, and > 70 years old), arsenic levels increase significantly with age (r = 0.166, p < 0.001, N = 25,547) (Fig. 3A). A similar relationship can be seen between age and lead level (r = 0.450, p < 0.001, N = 52,082) (Fig. 3C). Although mercury levels also correlate with age (r = 0.166, p < 0.001, N = 52,961), the increase stops at 50–60 years and even decreases slightly in older age groups (Fig. 3E).
Correlation between metals and age, also considering sex subgroups. Each data point represents mean +/- SEM.
In the age subgroup analysis, all three metals correlated with age in the 40–50 and 50–60 subgroups; lead was associated with age in all age subgroups, except in the 20-30-year-old group; mercury was not associated with age in the 60–70 and > 70 age subgroups (Table 5). In the sex subgroups, Spearman’s correlation showed that arsenic (males: r = 0.172, p < 0.001, N = 10,062; females: r = 0.161, p < 0.001, N = 15,471), lead (males: r = 0.386, p < 0.001, N = 19,840; females: r = 0.490, p < 0.001, N = 32,221), and mercury (males: r = 0.163, p < 0.001, N = 19,902; females: r = 0.164, p < 0.001, N = 33,037) significantly correlate with age in both men and women (Fig. 3B, D, F). Because there were only 28 outpatients of unknown sex (Table 1) and not all data on metals and eGFR was available, these patients were excluded from this correlation analysis.
Correlation of arsenic, lead, and mercury with eGFR
Supplementary Fig. 1 showed that arsenic (r= -0.131, p < 0.001, N = 11,211), lead (r= -0.318, p < 0.001, N = 21,733), and mercury (r= -0.149, p < 0.001, N = 22,670) all inversely correlate with eGFR in our study. With an increasing arsenic concentration, eGFR decreased (Fig. 4); up to a concentration of about 0.8–1.0 µg/L. At higher arsenic concentrations, eGFR plateaued. A similar trend was seen for lead and mercury – at a certain lead and mercury concentration eGFR also did not fall further (Fig. 4). Multivariate linear regression showed that arsenic (unstandardized coefficient B: -0.224, p = 0.043), lead (unstandardized coefficient B: -0.031, p = 0.025), and mercury (unstandardized coefficients B: -0.392, p < 0.001) correlated inversely with eGFR independently of the confounding factors age, sex, CRP, and fasting glucose (Tables 2, 3 and 4). Multivariate linear regression analysis in the subgroups of patients with eGFR above 60 mL/min for arsenic and mercury are significantly correlated with eGFR (Supplementary Tables 1–6).
Correlation between metals (low concentration range) and eGFR. Metal concentrations were grouped into ten different metal concentration groups: Arsenic and Mercury: 0-0.1; 0.1–0.2; 0.2–0.3; 0.3–0.4; 0.4–0.5; 0.5–0.6; 0.6–0.7; 0.7–0.8; 0.8–0.9; 0.9–1.0 µg/L. Lead: 0–5; 5–10; 10–15; 15–20; 20–25; 25–30; 30–35; 35–40; 40–45; 45–50 µg/L. Each data point represents mean +/- SEM.
Interaction of the effects of arsenic, lead, and mercury on kidney function
To examine the potential interaction effects of heavy metals on kidney function, we categorized the concentrations of each metal into two groups based on the median value: one group with concentrations below the median (Low) and another with concentrations above the median (Elevated). We then analysed the interactions between these groups (Table 5).
Figure 5 shows the effects of arsenic and lead on eGFR.
3D Plot-Effects of Arsenic and Lead on eGFR. The patients were divided into four groups according to the median of the metal concentrations: Group 1: Low Lead/Low Arsenic: eGFR ± SEM: 96.33 ± 0.158 ml/min/1.73m2, N = 15,832. Group 2: Low Lead/ Elevated Arsenic: eGFR ± SEM: 95.89 ± 0.124 ml/min/1.73m2, N = 25,670. Group 3: Elevated Lead/Low Arsenic: eGFR ± SEM: 89.92 ± 0.141 ml/min/1.73m2, N = 17,339. Group 4: Elevated Lead/ Elevated Arsenic; eGFR ± SEM: 91.83 ± 0.116 ml/min/1.73m2, N = 27,177. Group 1 versus group 4: p < 0.001. Group 2 versus group 4: p < 0.001. Group 3 versus group 4: p = 0.017.
Figure 6 illustrates the effects of arsenic and mercury on eGFR,
3D Plot-Effects of Arsenic and Mercury on eGFR. The patients were divided into four groups according to the median of the metal concentrations: Group 1: Low Arsenic/Low Mercury: eGFR ± SEM: 94.97 ± 0.158 ml/min/1.73m2, N = 16,650. Group 2: Low Arsenic / Elevated Mercury: eGFR ± SEM: 91.43 ± 0.138 ml/min/1.73m2, N = 17,182. Group 3: Elevated Arsenic /Low Mercury: eGFR ± SEM: 93.63 ± 0.157 ml/min/1.73m2, N = 16,376. Group 4: Elevated Arsenic / Elevated Mercury; eGFR ± SEM: 90.07 ± 0.134 ml/min/1.73m2, N = 16,908. Group 1 versus group 4: p < 0.001. Group 2 versus group 4: p < 0.001. Group 3 versus group 4: p < 0.001.
Figure 7 demonstrates the effects of lead and mercury on eGFR.
3D Plot-Effects of Lead and Mercury on eGFR. The patients were divided into four groups according to the median of the metal concentrations: Group 1: Low Mercury /Low Lead: eGFR ± SEM: eGFR: 96.24 ± 0.142 ml/min/1.73m2, N = 21,042. Group 2: Low Mercury / Elevated Lead: eGFR ± SEM: eGFR: 91.32 ± 0.131 ml/min/1.73m2, N = 22,549. Group 3: Elevated Mercury /Low Lead: eGFR ± SEM: eGFR: 93.39 ± 0.130 ml/min/1.73m2, N = 21,574. Group 4: Elevated Mercury / Elevated Lead; eGFR ± SEM: eGFR: 88.77 ± 0.115 ml/min/1.73m2, N = 23,081. Group 1 versus group 4: p < 0.001. Group 2 versus group 4: p < 0.001. Group 3 versus group 4: p < 0.001.
The interaction of metals—arsenic, lead, and mercury—on estimated glomerular filtration rate (eGFR) is notable for its compounding nephrotoxic effects, as demonstrated in the study data from Figs. 5, 6 and 7; Tables 6, 7 and 8. The findings reveal that combined exposure to these metals results in a greater decrease in eGFR compared to exposure to each metal individually, underscoring a potential synergistic toxicity. For instance, Fig. 5 shows that patients with both elevated lead and arsenic levels had a significantly lower eGFR (91.83 ml/min/1.73 m²) compared to those with lower concentrations (96.33 ml/min/1.73 m²), a statistically significant difference (p < 0.001). This pattern holds for arsenic-mercury (Fig. 6) and lead-mercury interactions (Fig. 7), suggesting that kidney function diminishes as exposure levels increase.
Multivariate regression analysis shows that combined high-level exposure to arsenic and lead (p = 0.002), arsenic and mercury (p < 0.001), and lead and mercury (p < 0.001) independently correlates with a lower eGFR, even after adjusting for confounders such as age, sex, and glucose levels (Tables 6, 7 and 8).
In summary, the combined exposure to these metals appears to exacerbate renal impairment, as evidenced by the decreased eGFR values across different groupings.
Environmental toxins may act on the human body in a sex-dependent manner, which is why we considered sex as a confounding factor in the multivariate analysis and in addition analyzed the relationship between metal concentrations and eGFR in women and men separately. Overall, this analysis revealed no major differences concerning the renal effects of these metals between women and men (Supplementary Fig. 2).
Figure 8 shows the correlation of eGFR and toxic metal concentrations in age tertiles of the participants indicating a particularly pronounced inverse relationship in the lowest age tertile. To illustrate the effects of age and sex for the effects of metal concentrations on eGFR, we additional created subgroup analysis (see supplementary Figs. 3–14.): These 3D plots (Supplementary Figs. 3–5, Female Group): illustrate the effects of metal combinations (Arsenic-Lead, Arsenic-Mercury, Lead-Mercury) on eGFR in females. The plots show a decrease in eGFR with elevated levels of each metal combination, highlighting the compounded nephrotoxic effects in female participants.
Correlation between metals and eGFR in Tertile Age subgroups. Correlation analysis by tertiles of age of the study participants (age ≤ 45 years old, 45 < Age ≤ 58.4 years old, Age > 58.4 years old) and analyzed by spearman correlation.
Analysis of metal combinations with eGFR for male participants are shown in Supplementary Figs. 6–8). Findings were comparable to those seen in female study participants. In Supplementary Figs. 9–11 analysis of metal interactions in older subjects (age above the median of the entire study population) are shown. Supplementary Figs. 12–14 shows similar analysis in participants whose age was below the median age of the study population.