Zhang Yun-rui, Wang Ping, Liang Xu-xia, Tan Chuen Seng, Tan Jian-bin, Wang Jing, Huang Qiong, Huang Rui, Li Zhi-xue, Chen Wen-cai, Wu Shi-xuan, Ong Choon Nam, Yang Xing-fen, Wu Yong-ning
Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China.
Department of Occupational and Environmental Health, Medical School, Ji'Nan University, Guangzhou 510632, China.
Int J Environ Res Public Health. 2015 Sep 24;12(10):11988-2001. doi: 10.3390/ijerph121011988.
The aim of this study was to systematically evaluate the relationship between urinary excretion of cadmium (U-Cd) and biomarkers of renal dysfunction.
One hundred eighty five non-smoking female farmers (aged from 44 to 71 years) were recruited from two rural areas with different cadmium levels of exposure in southern China. Morning spot urine samples were collected for detecting U-Cd, urinary creatinine (U-cre), β₂-microglobulin (β₂-MG), α₁-microglobulin (α₁-MG), metallothionein (MT), retinol binding protein (RBP), albumin (AB), N-acetyl-β-D-glucosaminidase (NAG), alkaline phosphatase (ALP), γ-glutamyl transpeptidase (GGT) and kidney injury molecule-1 (KIM-1). Spearman's rank correlation was carried out to assess pairwise bivariate associations between continuous variables. Three different models of multiple linear regression (the cre-corrected, un-corrected and cre-adjusted model) were used to model the dose-response relationships between U-Cd and nine urine markers.
Spearman's rank correlation showed that NAG, ALP, RBP, β₂-MG and MT were significantly associated with U-Cd for both cre-corrected and observed data. Generally, NAG correlated best with U-Cd among the nine biomarkers studied, followed by ALP and MT. In the un-corrected model and cre-adjusted model, the regression coefficients and R² of nine biomarkers were larger than the corresponding values in the cre-corrected model, indicating that the use of observed data was better for investigating the relationship between biomarkers and U-Cd than cre-corrected data.
Our results suggest that NAG, MT and ALP in urine were better biomarkers for long-term environmental cadmium exposure assessment among the nine biomarkers studied. Further, data without normalization with creatinine show better relationships between cadmium exposure and renal dysfunction.
本研究旨在系统评估尿镉排泄量(U-Cd)与肾功能障碍生物标志物之间的关系。
从中国南方两个镉暴露水平不同的农村地区招募了185名不吸烟的女性农民(年龄在44至71岁之间)。收集晨尿样本以检测U-Cd、尿肌酐(U-cre)、β₂-微球蛋白(β₂-MG)、α₁-微球蛋白(α₁-MG)、金属硫蛋白(MT)、视黄醇结合蛋白(RBP)、白蛋白(AB)、N-乙酰-β-D-氨基葡萄糖苷酶(NAG)、碱性磷酸酶(ALP)、γ-谷氨酰转肽酶(GGT)和肾损伤分子-1(KIM-1)。采用Spearman秩相关分析来评估连续变量之间的成对双变量关联。使用三种不同的多元线性回归模型(肌酐校正模型、未校正模型和肌酐调整模型)来模拟U-Cd与九种尿标志物之间的剂量反应关系。
Spearman秩相关分析表明,对于肌酐校正数据和实测数据,NAG、ALP、RBP、β₂-MG和MT与U-Cd均显著相关。总体而言,在所研究的九种生物标志物中,NAG与U-Cd的相关性最佳,其次是ALP和MT。在未校正模型和肌酐调整模型中,九种生物标志物的回归系数和R²均大于肌酐校正模型中的相应值,表明使用实测数据比肌酐校正数据更有利于研究生物标志物与U-Cd之间的关系。
我们的结果表明,在所研究的九种生物标志物中,尿中的NAG、MT和ALP是评估长期环境镉暴露的更好生物标志物。此外,未经肌酐标准化的数据显示镉暴露与肾功能障碍之间的关系更好。