Grantee Research Project Results

2004 Progress Report: Biomarker Application and Risk Assessment of Cr(VI)

EPA Grant Number: R830682
Title: Biomarker Application and Risk Assessment of Cr(VI)
Investigators: Qu, Qingshan , Shore, Roy E. , Cohen, Beverly S. , An, Feiyun , Costa, Max
Institution: New York University School of Medicine , Central South University School of Public Health - China
EPA Project Officer: Hahn, Intaek
Project Period: September 1, 2002 through August 31, 2005
Project Period Covered by this Report: September 1, 2003 through August 31, 2004
Project Amount: $898,601
RFA: Issues in Human Health Risk Assessment (2001) RFA Text |  Recipients Lists
Research Category: Human Health

Objective:

Cr(VI) is one of the major contaminants at numerous Superfund sites and is a well established human carcinogen. It is difficult, however, to estimate the risk in humans with exposures to Cr(VI) at low levels. The objective of this research project is to evaluate how biomarkers can be used to make direct and reliable health risk assessment of Cr(VI) in humans at low ambient exposure levels.

Progress Summary:

The work conducted in both China and the United States during Year 2 of the project progressed very well. The work completed so far includes:

1. recruitment of 145 subjects, including 30 unexposed and 115 exposed workers;
2. personal exposure monitoring for all recruited subjects and analyses for Cr in all personal samplers;
3. analyses of Cr levels in red blood cells (RBC) collected from all subjects;
4. assays for DNA-protein cross-links (DPC) in blood samples;
5. single cell gel electrophoresis (Comet assay) to detect DNA damage;
6. 8-hydroxydeoxyguanosine (8-OHdG) analysis in urine;
7. cotinine and creatinine analyses in all urine samples collected;
8. and identification of polymorphisms of hOGG1 (base excision repair gene) and GPX1 (antioxidative gene encoding for glutathione peroxidase) for all 196 subjects recruited in both Years 1 and 2 of the project.

In addition, a pilot project of proteomic analyses using Ciphergen SELDI ProteinChip technology also was conducted in 10 exposed and 10 unexposed subjects for discovery of potential new protein biomarkers of Cr(VI) exposure and associated biological effects. The results obtained are summarized below.

Subjects and Personal Exposure Levels

A total of 196 subjects were recruited in Years 1 and 2 of the project and screened for Cr(VI) by questionnaire, physical examination, and personal exposure monitoring. Among them, 141 subjects are workers identified from a chromate plant with average Cr(VI) exposure of 62.8 µg/m³. Fifty-five unexposed subjects were recruited in an area that is 50 to 60 miles away from the chromate facility. Demographic characteristics and smoking status among exposed and unexposed subjects were similar (Table 1).

Table 1. Demographic Characteristics and Personal Exposure Levels of Subjects

	Gender Female (%)	Age	Cotinine (mg/g creatinine)	Cr(VI) Exposure (µg/m3)
Unexposed Exposed	21.8 27.7	34.8 ± 5.3 35.7 ± 5.9	1.63 ± 2.32 1.60 ± 2.74	0.09 ± 0.11 62.75 ± 139.93

The Exposure Biomarker–Cr in RBC

Cr levels in RBC were determined by graphite furnace atomic absorption with Zeeman background correction. The levels of Cr in RBC were significantly higher in exposed workers (12.4 ± 20.1 g/L RBC) compared to unexposed subjects (2.8 ± 1.7 g/L RBC; P < 0.0001) and showed a significant exposure-response trend (Figure 1). Further analyses of Cr in RBC versus personal exposure levels, controlling for age, sex, and smoking status as possible confounders, continued to show strong association (P < 0.0001). All the findings suggest that Cr in RBC is a sensitive and reliable marker for Cr(VI).

Figure 1. Association of Cr in RBC With Personal Exposures to Cr(VI)

Changes of Biological Effect Markers

As shown in Table 2, the scores of the Comet assay were well associated with personal exposure levels of Cr(VI). Statistical analysis indicated that the scores of Comet assay in the lowest exposed group were significantly higher than the scores in the unexposed subjects (p < 0.0001).

The levels of DPC were significantly higher in the exposed group compared to the unexposed group (P < 0.01, not shown). No significant difference, however, was detected in DPC levels between unexposed subjects and the first three exposed groups, suggesting that DPC may not be a sensitive marker for Cr(VI) exposure at or below 0.030 mg/m³ (Table 2).

It was observed that urinary 8-OHdG correlated very well with personal exposures to Cr(VI) (p < 0.0001). Further analysis indicated that the levels of 8-OHdG were significantly higher in the lowest exposed group than in the unexposed group (p < 0.05), suggesting that it may be a useful biomarker for Cr(VI) exposure at or below 0.005 mg/m³.

Table 2. Levels of Biological Effect Markers in Subjects Grouped According to Cr(VI) Exposures

	Unexposed N = 55	< 5 µg/m3 N = 27	< 15 µg/m3 N = 37	< 30 µg/m3 N = 28	≥ 30 µg/m3 N = 49
Comet Scores	20.6 ± 13.5	47.9 ± 20.5A	53.0 ± 23.1	51.2 ± 19.3	61.9 ± 20.4C
DPC (% total DNA)	1.95 ± 1.08	1.81 ± 0.86	1.96 ± 0.75	2.60 ± 1.56	3.09 ± 1.65B,C
8-OHdG (mg/g creat)	0.08 ± 0.16	0.28 ± 0.43B	0.61 ± 0.71	0.50 ± 0.68	0.86 ± 0.80D
A significantly different from unexposed subjects, P < 0.0001.
B significantly different from unexposed subjects, P < 0.05.
C,D test for exposure-response trend, P < 0.01 and < 0.0001, respectively.

Potential Genetic Susceptibility Factors

The genotypes of hGPX1, MnSOD, and hOGG1 were identified in all recruited subjects to examine their potential roles in determining individual susceptibility to Cr(VI) exposure. The multiple regression analyses suggested that subjects with hOGG1 variant alleles were susceptible to Cr(VI)-induced DNA damages detected by comet assay (Table 3). The heterozygous alleles of either hGPX1 Pro197Leu or Pro198Leu polymorphisms made people susceptible to Cr(VI)-associated DPC (Tables 4 and 5).

Table 3. Multiple Regression Analyses of Comet Scores on Cr in RBC Adjusted for Sex, Age, Cotinine, and hOGG1 Genotypes

	Estimate	SE	P Value
Intercept Sex Age Cr in RBC Cotinine h OGG1	6.9965 -0.4618 0.3481 27.4512 0.5814 4.8502	13.6234 4.3237 0.2693 3.6945 1.7619 2.1996	0.6082 0.9150 0.1974 0.0000 0.7148 0.0287

Table 4. Multiple Regression Analyses of DPC on Cr in RBC Adjusted for Sex, Age, Cotinine, and hGPX1 Pro197Leu Polymorphism

	Estimate	SE	P Value
Intercept Sex Age Cr in RBC Cotinine h GPX1 Pro197Leu	1.6767 -0.2600 0.0017 1.3578 -0.1103 0.3752	0.7569 0.2450 0.0152 0.2077 0.0984 0.1778	0.0279 0.2899 0.9094 0.0000 0.2636 0.0362

Table 5. Multiple Regression Analyses of DPC on Cr in RBC Adjusted for Sex, Age, Cotinine, and hGPX1 Pro198Leu Polymorphism

	Estimate	SE	P Value
Intercept Sex Age Cr in RBC Cotinine h GPX1 Pro198Leu	1.5791 -0.2424 0.0084 1.2974 -0.1146 0.4845	0.7586 0.2436 0.0153 0.2062 0.0984 0.2217	0.0387 0.3211 0.5828 0.0000 0.2456 0.0301

A Pilot Project: Screening for Potential Protein Markers of Cr(VI)

The proteomic univariate analyses first discovered 55 individual mass/charge ratio (m/z) peaks that showed significant differences between the two groups. Furthermore, multiple regression analyses revealed that 30 out of the 55 peaks were still significantly associated with Cr levels in RBC after adjustment by age and cotinine levels. A summary of the multiple regression analyses on eight representative peaks is given in Table 6. The intensities of these peaks were all strongly associated with Cr levels in RBC with P values less than 0.01. Age and smoking status did not show any significant confounding effect on protein peak intensity except the m/z 118927 peak.

Table 6. Multiple Regression Analyses of Protein Peaks on Cr in RBC Adjusted With Age and Cotinine Levels. The data shown in the table are P values.

	118927A	149082	44603	3340	4442	7782	7981	8162
Intercept	0.000	0.004	0.000	0.199	0.387	0.199	0.017	0.0068
Age	0.002	0.718	0.340	0.178	0.309	0.131	0.366	0.0705
Cotinine	0.042	0.149	0.853	0.816	0.845	0.534	0.746	0.5275
Cr in RBC	0.001	0.003	0.01	0.009	0.006	0.000	0.000	0.001
A m/z value of the protein peak

Further statistical analyses were conducted on three proteins (m/z 7782, 7981, and 8162 peaks) with P values less than 0.001 to examine their exposure response relationship and correlations with other biological effect markers. All three peaks showed significant differences between the two groups and clear-cut exposure-dependent decreases with Cr levels in RBC (Figure 2). These peaks also were found to correlate with other biological effect markers we measured, including DPC, comet assay scores, and urinary 8-OHdG (Table 7).

Figure 2. Associations of the Three Identified Proteins With Cr Levels in RBC. A: m/z 7782, B: m/z 7981, C: m/z 8162.

Table 7. Correlations Between Identified Protein Peaks and Other Biological Effect Markers*

	Comet Scores	DPC	8-OHdG
m/z 7782 peak m/z 7981 peak m/z 8162	0.48 (0.03) 0.58 (0.007) 0.55 (0.01)	0.74 (0.0002) 0.62 (0.004) 0.53 (0.02)	0.72 (0.0005) 0.69 (0.001) 0.61 (0.006)
*The outcomes were expressed as r (P value)

Future Activities:

According to the original plan, we will conduct a time-course study, using a small group of subjects with Cr(VI) exposures. It will be difficult to conduct a time course study for Cr in blood, especially in blood cells among workers, because the maximal periods for workers without exposure are only two days (Saturday and Sunday after Friday’s exposure). We will try, however, to make a special arrangement with both personnel managers and workers who are expected to retire soon (workers retire at age 55 in China). Accordingly, 5 to 10 to-be-retired-workers will be recruited by interacting with personnel managers and workers. The recruited workers will be monitored for personal exposure to Cr(VI) on the last day before retirement. The first blood samples will be collected from each individual at the end of the workshift (0 hour) and followed by sample collections on days 1, 7, 15, 30, 60, 90, 120, and 180 after cessation of exposure. These blood collection strategies should provide a good characterization of clearance kinetics and permit us to calculate the half-lives of the relevant biomarkers.

An in vitro project for identifying the most susceptible pattern of genotype combination is underway. Among the 196 subjects recruited so far, 4 groups of subjects (9 in each group) were identified with different genotype combinations of hOGG1 and hGPX1 as listed in Table 8.

Table 8. Subjects Identified for In Vitro Study to Identify the Most Susceptible Genotype or Combination of Genotypes

Groups hypothesis	hGPX1 Pro 197Leu	hOGG1
A: most susceptible	W/V*	V/V
B: most resistant	W/W	W/W
C: between A and B	W/W	V/V
D: between A and B	W/V	W/W
* W/W: homozygous wild type; W/V: heterozygous alleles; V/V: homozygous variant alleles.

The lymphocytes isolated from the blood samples from these subjects will be treated first with phytohemagglutinin and then incubated with various doses of sodium dichromate for 4 hours. One aliquot of cultured lymphocytes will be harvested right after cessation of Cr incubation for bioassays of DNA damages. The leftover lymphocytes will be incubated with fresh medium for an additional 24 hours to further examine DNA damages following the DNA repair process. The results are expected to confirm the findings of single genetic susceptibility factors discussed above and further identify the most susceptible combinations of genotypes.

A validation project with relatively large number of samples (30 x 30) is in progress and expected to confirm the findings in the pilot project. This project may lead to further purification, identification, and assay development of the candidate protein markers that can be used for evaluation of Cr(VI)-associated health hazards and risk assessment in human populations.

Journal Articles:

No journal articles submitted with this report: View all 2 publications for this project

Supplemental Keywords:

chromium, Cr(VI), exposure, biomarker, proteomics, ProteinChip technology, heavy metal, biological monitoring, risk analysis, hazardous waste, hexavalent chromium, human exposure, human health risk,, RFA, Health, Scientific Discipline, INTERNATIONAL COOPERATION, Waste, Hazardous, Health Risk Assessment, Risk Assessments, Biology, hexavalent chromium, Hazardous Waste, Biochemistry, hexavalent chromium waste, human exposure, children's health, exposure, hazardous waste characterization, superfund site, human health risk, biomarker

Progress and Final Reports:

Original Abstract

2003

Final