Validation of PAH Biomarkers for Quantifying Cancer Risk
Validation of PAH Biomarkers for Quantifying Cancer Risk
批准号:
6522503
负责人:
JUNFENG ZHANG
金额:
$21.05万
依托单位国家:
美国
项目类别:
财政年份:
2001
资助国家:
美国
项目状态:
已结题
起止时间:
2001-09-30 至 2004-08-31
中文摘要
描述(由申请人提供):
生物监测对于评估暴露于
存在的污染物,如多环芳烃(PAHs)
在多种环境媒体中。尽管一些多环芳烃生物标志物已经被
将癌症死亡率与平均死亡率联系起来的已开发的流行病学研究
生物标记物浓度缺乏;目前的风险评估框架是
基于空气中苯并[a]芘(BaP)的浓度。建议的目标是
研究是为了填补阻碍应用的几个重要空白
多环芳烃生物标记物在量化癌症风险中的作用。两个尿液标志物,
1-羟基并[a]芘和9-羟基苯并[a]芘将被特别验证
为此目的,通过实现以下具体目标。目标1是
建立尿药浓度与BaP之间的定量关系
暴露量将以24小时平均个人空气浓度和
24小时膳食摄入量。目标2是检查是否存在显著的
研究对象的尿标志物浓度的逐日变化
每天稳定的多环芳烃暴露。这一点很重要,因为对于一个生物标志物来说
对于估计癌症风险很有用,这个标记物应该能够预测
人们的平均(稳定)暴露。目标3是检查第一个
晨尿样本可以有效地代表每日接触或24小时
需要复合尿样。这一点具有实际意义,因为
在自由生活的人群中,24小时尿样的获取难度要大得多。
目标4是检查尿标志物和其他PAH之间的关系
指标,因为PAH混合物的其他指标可能被证明是更好的指标
用于未来的风险评估。这项研究将在100名无烟者中进行
广泛接触空气传播的苯系物的成年人,包括
职业和非职业暴露的个人。这是必要的
为了评估这些生物标记物在更广泛的应用中的有效性,
因为高PAH暴露不仅会发生在许多职业环境中
而且在其他人的日常生活中也是如此,包括不吸烟的人。这项研究
将由每个受试者的两组重复测量组成。每套
测量的范围包括:24小时个人呼吸区浓度
气相和颗粒相多环芳烃;24小时膳食多环芳烃摄入量;生物标志物
第一次晨尿和24小时混合尿中的浓度。所有这些都是
测量将在相同的24小时内进行。两个重复的
对于每个受试者,测量将至少间隔三个月
最大限度地提高日常暴露的代表性。空气样本和食物
样本将被分析至少16种常见的多环芳烃,包括芘和苯并(A)苯
使用已建立的高效液相色谱/荧光分析方法。尿液斑点状的性质
血药浓度将用肌酐进行校正。统计方法有待改进
使用的内容包括描述性分析、散点图、相关分析、
配对比较和线性混合模型。在混合模型中,年龄,性别,
身高、体重和体重指数将进行调整。
英文摘要
DESCRIPTION (provided by applicant):
Biological monitoring is particularly useful for assessing exposure to
pollutants, such as polycyclic aromatic hydrocarbons (PAHs), that are present
in multiple environmental media. Although a number of PAH biomarkers have been
developed, epidemiological studies relating cancer mortality to average
biomarker concentrations are lacking; and the current risk assessment frame is
based on air concentrations of benzo[a]pyrene (BaP). The goal of the proposed
study is to fill in several important gaps that have hampered the application
of PAH biomarkers in quantifying cancer risk. Two urinary markers,
1-hydroxypyrene and 9-hydroxy-benzo[a]pyrene, will be specifically validated
for this purpose through achieving the following specific aims. Aim 1 is to
establish a quantitative relationship between urinary concentrations and BaP
exposure which will be measured as 24-h average personal air concentration and
24-h dietary intake. Aim 2 is to examine whether there is a significant
day-to-day variation in urinary marker concentrations in study subjects having
stable daily PAH exposures. This is important because for a biomarker to be
useful for estimating cancer risk, this marker should be able to predict
people's average (steady) exposure. Aim 3 is to examine whether a first
morning urine sample can efficiently represent daily exposure or a 24-hour
composite urine sample is required. This is of practical importance because
24-h urine samples are considerably harder to get in free-living populations.
Aim 4 is to examine relationships between urinary markers and other PAH
metrics, because other metrics of PAH mixture may prove to be a better index
for future risk assessment. The study will be carried out in 100 non-smoking
adults with a wide range of exposure to airborne BaP, including both
occupationally and non-occupationally exposed individuals. This is necessary
to evaluate the effectiveness of these biomarkers in a broader application,
because high PAH exposures can occur not only in many occupational settings
but also in the daily lives of other people, including non-smokers. The study
will consist of two sets of repeated measurements for each subject. Each set
of the measurement will include: 24-h personal breathing-zone concentrations
of gas-phase and particle-phase PAHs; 24-h dietary PAH intakes; biomarker
concentrations in first morning urine and in 24-h composite urine. All these
measurements will be made within the same 24-h period. Two repeated
measurements will be separated by at least three months for each subject to
maximize the representativeness of daily exposure. Air samples and food
samples will be analyzed for at least 16 common PAHs including pyrene and BaP
using the established HPLC/fluorescence methods. The spot nature of urinary
concentrations will be corrected with creatinine. Statistical methods to be
used will include descriptive analyses, scatter plots, correlation analyses,
paired comparisons, and linear mixed models. In the mixed models, age, sex,
height, weight, and body mass index will be adjusted for.
期刊论文(0)
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