因为与慢性砷暴露相关的一些不良健康影响可能是由甲基化砷化物介导的,将无机砷转化为单甲基化和二甲基化代谢物的能力的个体间差异可能是与暴露于这种准金属相关的风险的重要决定因素。因此,识别改变个体对无机砷的甲基化能力的生物学和行为因素可以提供对潜在的不良健康影响的关键剂量-反应关系的见解。
丘吉尔县共有904名老年人(≥45岁),内华达,长期使用每升砷含量高达1850μg的家庭自来水的人提供了尿液和脚趾甲样品,用于测定总砷和特定砷含量。生物因素的影响(性别,年龄,体重指数)和行为因素(吸烟,使用双变量分析和多元回归模型评估了最近的鱼类或贝类消费)对尿液中砷的模式。
无机的相对贡献,mono-,在研究参与者使用的家用自来水中砷的浓度范围内,尿液中的二甲基化砷占总形态砷的比例没有变化。性别可以预测尿液中砷的绝对和相对含量。年龄预测尿液中无机砷的水平和体重指数预测尿液中单甲基化和二甲基化砷的相对水平。吸烟可预测尿液中砷的绝对和相对水平。建立了尿液中砷的绝对和相对水平的多元回归模型。家用自来水中砷的浓度和估计的水消耗量强烈预测了尿液中砷的含量,吸烟也是如此。身体质量指数,和性别。砷对尿砷的相对贡献并不是通过饮用水中砷的浓度来预测的,而是通过性别来预测的。身体质量指数,年龄,和吸烟。
这些发现表明,对砷暴露人群的剂量-反应关系的分析应考虑改变尿液中无机和甲基化砷含量的生物学和行为因素。这些因素对砷代谢产生重大影响的证据也可能支持在适当的实验模型中进行的作用模式研究。
Because some adverse health effects associated with chronic arsenic exposure may be mediated by methylated arsenicals, interindividual variation in capacity to convert inorganic arsenic into mono- and di-methylated metabolites may be an important determinant of risk associated with exposure to this metalloid. Hence, identifying biological and behavioral factors that modify an individual\'s capacity to methylate inorganic arsenic could provide insights into critical dose-response relations underlying adverse health effects.
A total of 904 older adults (≥45 years old) in Churchill County, Nevada, who chronically used home tap water supplies containing up to 1850 μg of arsenic per liter provided urine and toenail samples for determination of total and speciated arsenic levels. Effects of biological factors (gender, age, body mass index) and behavioral factors (smoking, recent fish or shellfish consumption) on patterns of arsenicals in urine were evaluated with bivariate analyses and multivariate regression models.
Relative contributions of inorganic, mono-, and di-methylated arsenic to total speciated arsenic in urine were unchanged over the range of concentrations of arsenic in home tap water supplies used by study participants. Gender predicted both absolute and relative amounts of arsenicals in urine. Age predicted levels of inorganic arsenic in urine and body mass index predicted relative levels of mono- and di-methylated arsenic in urine. Smoking predicted both absolute and relative levels of arsenicals in urine. Multivariate regression models were developed for both absolute and relative levels of arsenicals in urine. Concentration of arsenic in home tap water and estimated water consumption were strongly predictive of levels of arsenicals in urine as were smoking, body mass index, and gender. Relative contributions of arsenicals to urinary arsenic were not consistently predicted by concentrations of arsenic in drinking water supplies but were more consistently predicted by gender, body mass index, age, and smoking.
These findings suggest that analyses of dose-response relations in arsenic-exposed populations should account for biological and behavioral factors that modify levels of inorganic and methylated arsenicals in urine. Evidence of significant effects of these factors on arsenic metabolism may also support mode of action studies in appropriate experimental models.