| Literature DB >> 34444074 |
Kuo-Jung Ho1, Tzu-Hua Chen2, Chen-Cheng Yang3, Yao-Chung Chuang4, Hung-Yi Chuang5,6.
Abstract
Smoking and lead (Pb) exposure increased oxidative stress in human body, and people with some gene variants may be susceptible to Pb and smoking via oxidative stress. The aim of this study is to evaluate oxidative stress by measuring thiobarbituric acid reactive substances (TBARS) and the relationship of lipid peroxidation markers in Pb workers with different gene polymorphisms (rs4673 and rs1050450) in both smokers and nonsmokers. Blood samples were collected from 267 Pb workers who received their annual health examination in the Kaohsiung Medical University Hospital. Glutathione peroxidase 1 (GPx-1) rs1050450 and cytochrome B-245 Alpha Chain (CYBA) rs4673 single-nucleotide polymorphisms (SNP) were analyzed by specific primer-probes using Real-Time PCR methods. The interaction between blood Pb and smoking increased serum levels of TBARS and the ratio of oxidative low-density lipoprotein and low-density lipoprotein (oxLDL/LDL). Analysis of workers with rs1050450 SNPs showed higher blood Pb levels in the workers with CC genotype than those with CT genotype. Smokers had significantly higher blood Pb, alanine transaminase (ALT), TBARS, and OxLDL levels than nonsmokers. TBARS increased 0.009 nmol/mL when blood Pb increased one µg/dL in smokers compared to nonsmokers. The ratio of OxLDL/LDL increased 0.223 when blood Pb increased one µg/dL in smokers compared to nonsmokers. TBARS levels and the ratio of OxLDL/LDL were positively correlated and interacted between blood Pb and smoking after the adjustment of confounders, suggesting that smoking cessation is an important issue in the Pb-exposed working environment.Entities:
Keywords: CYBA; GPx-1; OxLDL; TBARS; lead; single nucleotide polymorphisms; smoke
Mesh:
Substances:
Year: 2021 PMID: 34444074 PMCID: PMC8393757 DOI: 10.3390/ijerph18168325
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Descriptive data of clinical and biochemical by smoking status.
| Variables | Smokers ( | Nonsmokers ( | |
|---|---|---|---|
| Blood Pb (μg/dL) | 22.11 ± 15.19 | 7.97 ± 10.42 | <0.001 ** |
| Age (years) | 43.7 ± 9.7 | 41.1 ± 10.4 | 0.058 |
| Sex (male) | 80 (98.8%) | 113 (60.8%) | <0.001 ** |
| Alcohol (>3 times/week) | 28 (42.4%) | 13 (7.3%) | <0.001 ** |
| BMI (kg/m2) | 25.69 ± 3.52 | 23.88 ± 3.71 | <0.001 ** |
| BMI < 18.5 | 3 (3.7%) | 7 (3.8%) | 0.981 |
| BMI ≥ 24 | 56 (69.1%) | 83 (44.6%) | 0.001 ** |
| Creatinine (mg/dL) | 1.22 ± 0.14 | 1.15 ± 0.63 | 0.357 |
| ALT (U/L) | 22.85 ± 14.42 | 18.19 ± 16.14 | 0.027 * |
| AC sugar (mg/dL) | 102.92 ± 33.41 | 99.54 ± 31.08 | 0.433 |
| TBARS (nmol/mL) | 2.289 ± 0.559 | 1.953 ± 0.351 | <0.001 ** |
| OxLDL (mg/dL) | 59.857 ± 14.567 | 53.76 ± 11.252 | 0.001 ** |
| LDL (mg/dL) | 104.621 ± 18.304 | 104.457 ± 11.625 | 0.942 |
| CYBA gene (rs4673) | 0.625 | ||
| CC | 60 (74.1%) | 145 (78.0%) | |
| CT | 19 (23.5%) | 39 (21.0%) | |
| TT | 2 (2.5%) | 2 (1.1%) | |
| GPX1 gene (rs1050450) | 0.157 | ||
| CC | 75 (92.6%) | 161 (86.6%) | |
| CT | 6 (7.4%) | 25 (13.4%) |
* p < 0.05, ** p < 0.01. p values were calculated by independent t test for continuous variables and chi-square test for categorical variables. Types of CYBA (rs4673) and GPX1 (rs1050450) in both smokers and nonsmokers groups were consistent with Hardy–Weinberg equilibrium. BMI = body mass index; ALT = alanine transaminase, AC sugar = fasting sugar; TBARS = thiobarbituric acid reactive substances; OxLDL = oxidative low-density lipoprotein; LDL = low-density lipoprotein; CYBA gene = cytochrome B-245 Alpha Chain gene; GPX1 gene = Glutathione peroxidase 1 gene.
Descriptive characteristics among the different types of CYBA rs4673 and GPx-1 rs1050450 SNPs.
| Variables | CYBA rs4673 | GPx-1 rs1050450 | |||||
|---|---|---|---|---|---|---|---|
| Mean ± SD or | CC ( | CT ( | TT ( | CC ( | CT ( | ||
| Blood Pb (μg/dL) | 11.82 ± 13.74 | 13.09 ± 12.75 | 23.04 ± 22.31 | 0.234 | 12.87 ± 14.03 | 7.58 ± 9.61 | 0.009 * |
| Age (years) | 42.1 ± 10.1 | 41.6 ± 11.2 | 35.6 ± 4.4 | 0.477 | 42.0 ± 10.3 | 40.9 ± 9.8 | 0.556 |
| Sex (male) | 148 (72.2%) | 41 (70.7%) | 4 (100%) | 0.448 | 171 (72.5%) | 22 (71.0%) | 0.862 |
| Current smoking | 60 (29.3%) | 19 (32.8%) | 2 (50%) | 0.605 | 75 (31.8%) | 6 (19.4%) | 0.157 |
| Alcohol (>3 times/week) | 32 (16.9%) | 9 (17.3%) | 0 (0%) | 0.734 | 38 (17.6%) | 3 (10.7%) | 0.36 |
| BMI (kg/m2) | 24.43 ± 3.72 | 24.48 ± 3.91 | 24.48 ± 2.55 | 0.875 | 24.51 ± 3.81 | 23.83 ± 3.14 | 0.343 |
| BMI < 18.5 | 8 (3.9%) | 2 (3.4%) | 0 (0%) | 0.912 | 9 (3.8%) | 1 (3.2%) | 0.871 |
| BMI ≥ 24 | 106 (51.7%) | 32 (55.1%) | 1 (25%) | 0.494 | 123 (52.1%) | 16 (51.6%) | 0.958 |
| Creatinine (mg/dL) | 1.18 ± 0.60 | 1.15 ± 0.18 | 1.17 ± 0.53 | 0.954 | 1.18 ± 0.59 | 1.10 ± 0.17 | 0.438 |
| ALT (U/L) | 19.7 ± 15.1 | 20.1 ± 18.3 | 11.0 ± 6.3 | 0.624 | 19.9 ± 16.2 | 17.8 ± 11.7 | 0.501 |
| AC sugar (mg/dL) | 98.9 ± 25.1 | 107.3 ± 49.0 | 90.2 ± 5.4 | 0.192 | 101.3 ± 33.3 | 94.8 ± 14.0 | 0.308 |
| TBARS(nmol/mL) | 2.06 ± 0.46 | 2.06 ± 0.41 | 1.72 ± 0.27 | 0.332 | 2.053 ± 0.464 | 2.078 ± 0.344 | 0.776 |
| OxLDL (mg/dL) | 55.98 ± 13.02 | 55.04 ± 11.26 | 45.87 ± 10.74 | 0.265 | 55.64 ± 12.92 | 55.50 ± 10.53 | 0.955 |
| LDL (mg/dL) | 105.31 ± 13.53 | 102.54 ± 14.89 | 93.07 ± 16.5 | 0.105 | 104.00 ± 14.10 | 108.39 ± 12.23 | 0.105 |
* p < 0.05. p values were calculated by independent t test for continuous variables and chi-square test for categorical variables.
Multiple linear regression coefficients of TBARS and OxLDL/LDL in different interaction models.
| Models | TBARS | OxLDL/LDL |
|---|---|---|
| β (SE) | β (SE) | |
| Model 1 | ||
| Blood Pb | −0.001 (0.003) | 0.078 (0.08) |
| smoking | 0.115 (0.101) | −0.704 (2.447) |
| Blood Pb x smoke | 0.009 (0.005) * | 0.223 (0.11) * |
| Model 2 | ||
| Blood Pb | 0.004 (0.003) | 0.193 (0.062) * |
| rs4673 | 0.003 (0.092) | 0.336 (2.219) |
| Blood Pb x rs4673 | −0.003 (0.005) | 0 (0.114) |
| Model 3 | ||
| Blood Pb | 0.004 (0.002) | 0.212 (0.058) ** |
| rs1050450 | 0.137 (0.114) | 2.054 (2.746) |
| Blood Pb x rs1050450 | −0.007 (0.009) | −0.317 (0.205) |
| Model 4 | ||
| Blood Pb | 0.004 (0.002) | 0.191 (0.057) ** |
| rs4673 | −0.055 (0.069) | 0.115 (1.67) |
| rs1050450 | 0.051 (0.104) | −1.278 (2.514) |
| rs4673 x rs1050450 | 0.1 (0.193) | 2.037 (4.66) |
| Model 5 | ||
| Blood Pb | 0.004 (0.002) | 0.192 (0.057) ** |
| rs4673 | −0.038 (0.067) | 0.433 (1.619) |
| rs1050450 | 0.09 (0.098) | −0.559 (2.352) |
| Blood Pb x rs4673 x rs1050450 | −0.003 (0.012) | −0.038 (0.285) |
* p < 0.05, ** p < 0.01, β (SE): regression coefficient and standard error.All models were adjusted for age, sex, BMI < 18.5, BMI ≥ 24 versus 18.5 ≤ BMI < 24, Cr > 1.5 versus Cr ≤ 1.5, ALT > 80 versus ALT ≤ 80, AC sugar ≥ 126 versus AC < 126.
Figure 1The interaction effect of smoking on the levels of TBARS and ratio of OxLDL/LDL in Pb-exposed workers. (a) The difference between the levels of TBARS was greater for smokers than nonsmokers in Pb-exposed workers. (p = 0.041). (b) The difference between the ratio of OxLDL/LDL was greater for smokers than for nonsmokers. (p = 0.044).