E-waste exposure elevated levels of biomarkers of CHD and OS in blood
Tn and MPO are markers of inflammation and CHD, respectively. In the present study, we analyzed the levels of Tn and MPO in blood. The results showed that the concentrations of the two biomarkers in the exposed group were significantly higher than those in the reference group (Table 2). Furthermore, we discovered that the concentrations of the two OS markers (MDA and 8-I) in the exposed group were significantly higher than those in the reference group.
Table 2
Concentrations of biomarkers (ng/mL) and heavy metals in blood from reference and exposed groups
| Reference group (Huangyan) | Exposed group(Luqiao) | P-value |
8-I (pg/ml) | 1021.72 | 1210.94 | 0.003 |
MDA(pg/mL) | 5.24 | 6.43 | 0.000 |
Tn(ng/mL) | 523.18 | 576.11 | 0.037 |
MPO(ng/mL) | 163.13 | 183.38 | 0.000 |
CHD is a chronic disease characterized by OS and inflammation. When the body is stimulated by external stimulation, the imbalance of OS result in the formation of significant amounts of lipid products and oxides in the arterial walls, which induces an immune response and an inflammatory reaction (Abraham and Marchuk 2014). Several studies have shown that MPO mediates the formation of OS and inflammatory reactions and is a significant inflammatory marker (Love et al. 2017; Zhang et al. 2020). Moreover, the oxidative modification of MPO causes the formation of arterial plaques, and the level of MPO is closely associated with CHD (Gorudko et al. 2012). During the initiation of CHD, inflammatory cell infiltration and OS can cause oxidative damage to cardiomyocytes and other tissues. When cardiomyocytes are slightly damaged, membrane rupture occurs, and Tn is released from the cardiomyocytes into the peripheral blood (Mair et al. 1994). Our results showed that e-waste exposure elevated the blood levels of CHD and OS biomarkers, i.e., Tn, MPO, 8-I, and MDA, which indicates an elevated risk of CHD in residents living near e-waste recycling sites, and that OS is involved in the process.
Associations Between Biomarkers And Heavy Metal Exposure
The results of the levels of the seven heavy metals in the blood samples are shown in Table 3. Compared with the reference group, the concentrations of Co, Ni, and Sn in the exposed group were significantly higher than those in the reference group (Table 3).
Table 3
Concentrations of heavy metals (ng/mL) in blood from reference and exposed groups
| Reference group (Huangyan) | Exposed group(Luqiao) | P-value |
Co | 0.32 | 0.40 | 0.000 |
Ni | 2.10 | 4.79 | 0.000 |
Cd | 1.56 | 1.60 | 0.892 |
Sn | 0.23 | 0.32 | 0.013 |
Cu | 735.14 | 763.85 | 0.261 |
Zn | 5312.01 | 4831.19 | 0.084 |
Pb | 32.85 | 37.93 | 0.066 |
SUM | 6084.21 | 5640.08 | 0.930 |
The results of Spearman correlation analysis showed that the concentrations of Co, Ni, and Sn were significantly positively correlated in the exposed group, indicating that the concentrations of heavy metals in human blood were affected by exposed e-waste. To investigate the contributions of heavy metals to the risk of CHD, we analyzed the relationships between altered heavy metals and biomarkers of CHD and OS using Spearman correlation analysis and multiple linear regression. In the exposed group, the Spearman correlation analysis showed that the concentration of Ni was positively correlated with the concentrations of Tn, MPO, MDA and 8-I. Meanwhile, the concentration of Co was positively correlated with 8-I and MDA, and 8-I and MPO were positively correlated with Sn (Table 4, Fig. 1). In addition, the linear regression analysis showed that Ni was correlated with Tn, MPO, and MDA, whereas Co was correlated with Tn (Table 5). In the reference group, both the Spearman correlation and linear regression analyses did not indicate any association between heavy metals and the biomarkers of CHD and OS (Tables 4 and 5).
Table 4
Spearman correlation coefficients among individual heavy metals and hormones in blood samples acquired from reference and exposed groups
| 8- I | MDA | Tn | MPO | Co | Ni | Sn |
Reference group | | | | | | | |
8-I | 1.000 | | | | | | |
p-value | | | | | | | |
MDA | 0.350* | 1.000 | | | | | |
p-value | 0.015 | | | | | | |
Tn | 0.162 | 0.145 | 1.000 | | | | |
p-value | 36 | 39 | 39 | | | | |
MPO | 0.230 | 0.100 | 0.314 | 1.000 | | | |
p-value | 0.138 | 0.51 | 0.052 | | | | |
Co | 0.256 | -0.16 | 0.016 | -0.075 | 1.000 | | |
p-value | 0.079 | 0.262 | 0.925 | 0.619 | | | |
Ni | -0.085 | -0.275 | -0.063 | -0.065 | 0.078 | 1.000 | |
p-value | 0.565 | 0.051 | 0.702 | 0.669 | 0.586 | | |
Sn | -0.160 | -0.245 | 0.029 | -0.047 | 0.104 | 0.298* | 1.000 |
p-value | 0.277 | 0.083 | 0.861 | 0.756 | 0.469 | 0.034 | |
exposed group | | | | | | | |
8-I | 1.000 | | | | | | |
p-value | . | | | | | | |
MDA | 0.399** | 1.000 | | | | | |
p-value | 0.002 | . | | | | | |
Tn | 0.166 | 0.018 | 1.000 | | | | |
p-value | 0.249 | 0.900 | . | | | | |
MPO | 0.331* | 0.132 | -0.013 | 1.000 | | | |
p-value | 0.018 | 0.357 | 0.928 | . | | | |
Co | 0.308* | 0.399** | -0.176 | 0.235 | 1.000 | | |
p-value | 0.020 | 0.002 | 0.209 | 0.091 | . | | |
Ni | 0.327* | 0.367** | .339* | 0.427** | 0.354** | 1.000 | |
p-value | 0.013 | 0.005 | 0.013 | 0.001 | 0.005 | . | |
Sn | 0.329* | 0.127 | 0.066 | 0.314* | 0.487** | 0.420** | 1.000 |
p-value | 0.012 | 0.348 | 0.639 | 0.022 | 0 | 0.001 | . |
*significance level of 0.1, **significance level of 0.05, ***significance level of 0.001. |
Table 5
Multiple linear regression analysis for analyzing associations between hormones and metals in participants of reference and exposed groups
| Reference group(Huangyan) | Exposed group(Luqiao) |
| β | 95% Cl | p-value | β | 95% Cl | p-value |
| MDA |
Ni | -0.240 | (-0.562) − 0.082 | 0.141 | 0.274 | (− 0.023) − 0.525 | 0.033 |
Co | -1.246 | (-3.993) − 1.500 | 0.366 | 1.932 | (− 0.026) − 3.890 | 0.053 |
Sn | -0.881 | (-2.397) − 0.635 | 0.248 | -0.238 | (-0.771) − 0.296 | 0.375 |
| 8-I |
Ni | -14.971 | (-94.64) − 64.707 | 0.707 | 48.533 | (-22.783) − 119.849 | 0.178 |
Co | 579.139 | (-15.682) − 1173.959 | 0.707 | 229.903 | (-327.439) − 787.246 | 0.412 |
Sn | -184.84 | (-517.551) − 147.872 | 0.056 | 5.126 | (-148.03) − 158.282 | 0.947 |
| Tn |
Ni | -5.615 | (-31.160) − 19.929 | 0.658 | 49.048 | 12.278–85.818 | 0.010 |
Co | 5.845 | (-250.984) − 262.673 | 0.963 | -556.678 | (-903.143) -(210.213) | 0.002 |
Sn | 17.518 | (-97.539) − 132.574 | 0.759 | 64.852 | ( -15.409) − 145.114 | 0.111 |
| MPO |
Ni | -1.459 | (-10.084) − 7.166 | 0.735 | 6.797 | 0.674–12.921 | 0.03 |
Co | -21.134 | (-108.193) − 65.924 | 0.627 | 7.018 | (-34.52) − 48.557 | 0.736 |
Sn | -3.670 | (-44.071) − 36.732 | 0.855 | -2.892 | (-14.085) − 8.302 | 0.606 |
Meanwhile, the results showed that exposure to heavy metals can affect OS in the body, as well as increase the corresponding levels of CHD markers. The results showed a significant correlation among MPO, 8-I, and MDA (Table 4).
Epidemiological and toxicological studies have shown that exposure to heavy metals is associated with cardiovascular mortality (Houston 2011). Heavy metals contribute significantly to CHD (Myong et al. 2014). Heavy metal-rich monocytes accumulate in the aortic wall through blood circulation and induce endothelial cell injury and apoptosis (Kukongviriyapan et al. 2014). Excessive amounts of heavy metals cause cardiotoxicity through apoptosis and DNA damage (Owumi et al. 2020). Metals can cause OS and inflammation, increase blood pressure, and affect thrombosis (Valera et al. 2012). After exposure to heavy metals, the body produces an inflammatory response, resulting in elevated levels of MPO, which increases the risk of CHD (Reisgen et al. 2020; Xiao et al. 2019). In a study pertaining to the cardiac toxicity of heavy metals, it was discovered that heavy metals can cause an increase in serum Tn levels (Ali et al. 2020). Our results showed that e-waste exposure elevated the blood levels of Ni, and that Ni was positively correlated with the biomarkers of CHD and OS, including Tn, MPO, MDA, and 8-I. Ni can promote LDL oxidation and affect AS (Wu et al. 2015). Furthermore, Ni damages the vascular endothelium and alters vasoconstriction/vasodilation, which are important symptoms of CHD (Cuevas et al. 2010). Occupational Ni exposure can increase lipid peroxidation and decrease antioxidant levels (Kalahasthi et al. 2006). Moreover, OS is vital to the pathogenesis of CHD (Yang et al. 2019). Elevated levels of MDA and 8-I suggest that exposure to heavy metals can result in lipid peroxidation, which can subsequently cause cell and tissue damage and hence the formation of plaques in the arteries. Based on the findings above, we infer that Ni can increase the risk of CHD and OS.