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Application of biological monitoring for exposure assessment following chemical incidents: A procedure for decision making

Journal of Exposure Science & Environmental Epidemiology volume 21, pages 247–261 (2011)Cite this article

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Abstract

Determination of the level of exposure during and after a chemical incident is crucial for the assessment of public health risks and for appropriate medical treatment, as well as for subsequent health studies that may be part of disaster management. Immediately after such an incident, there is usually no opportunity to collect reliable quantitative information on personal exposures and environmental concentrations may fall below detectable levels shortly after the incident has passed. However, many substances persist longer in biological tissues and thus biological monitoring strategies may have the potential to support exposure assessment, as part of health studies, even after the acute phase of a chemical incident is over. Reported successful applications involve very persistent chemical substances such as protein adducts and include those rare cases in which biological tissues were collected within a few hours after an incident. The persistence of a biomarker in biological tissues, the mechanism of toxicity, and the sensitivity of the analysis of a biomarker were identified as the key parameters to support a decision on the feasibility and usefulness of biological monitoring to be applied after an incident involving the release of hazardous chemicals. These input parameters could be retrieved from published methods on applications of biomarkers. Methods for rapid decision making on the usefulness and feasibility of using biological monitoring are needed. In this contribution, a stepwise procedure for taking such a decision is proposed. The persistence of a biomarker in biological tissues, the mechanism of toxicity, and the sensitivity of the analysis of a biomarker were identified as the key parameters to support such a decision. The procedure proposed for decision making is illustrated by case studies based on two documented chemical incidents in the Netherlands.

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Acknowledgements

This study was funded by the National Institute for Pubic Health and the Environment, The Netherlands. We express our gratitude to Dr. Paul Aston of AB Biomonitoring for his suggestions to improve the language of the manuscript. We are indebted to Dr. Peter Heitland and Dr. Hans-Wolfgang Hoppe of the Medizinisches Labor Bremen for supplying technical data concerning the analysis of biomarkers in body fluids.

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Authors and Affiliations

  1. Department of Epidemiology, Biostatistics and HTA, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands

    Paul T J Scheepers & Joke Konings

  2. National Institute for Public Health and the Environment, Bilthoven, The Netherlands

    Peter M J Bos, Nicole A H Janssen & Linda Grievink

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  1. Paul T J Scheepers
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  2. Peter M J Bos
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  3. Joke Konings
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  4. Nicole A H Janssen
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Correspondence to Paul T J Scheepers.

Additional information

Supplementary Information accompanies the paper on the Journal of Exposure Science and Environmental Epidemiology website (http://www.nature.com/jes)

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Appendix A

Appendix A

In this appendix we will describe how the elapsed time ts between the end of exposure during an incident and the last possible moment for sample collection can be calculated. We will make a distinction between two situations: first-order kinetics as typical for the elimination from body tissues of most parent compounds and their metabolites. For those biomarker that are captured in blood cells, such as hemoglobin adducts, we will also describe how to perform these calculations for biomarkers that follow zero-order kinetics. For both types of biomarkers, an example will be given.

C t s , which is defined as the concentration at the time of collection of biological tissues, should be equal to or above the limit of quantification:

LOQ indicates the minimum concentration of the biomarker at the time of sampling. It may be replaced by an alternative criterion for positive identification or by the 95 percentile background of the biomarker level in the general population if this value is substantially higher than the LOQ.

First-order elimination

When the biomarker is assumed to follow a log-linear decline in time, the value of this parameter at any time point ( C t s ) after cessation of the exposure can be described as:

In which Ce is the concentration of the biomarker at the end of the exposure and t1/2; is the half-life of this parameter (in hours), and ts is the time lapsed between the end of the exposure at the chemical incident location and the time when biological materials can be collected. Equations (1) and (2) can be rewritten as:

The second part of this equation ( 2 ( t s / t 1 / 2 ) ) indicates the factor by which the concentration at the end of exposure has decreased as a function of the number of half-lives that elapsed between the end of the exposure and the moment of sampling ts.

Case 1: Benzene

The example of benzene is elaborated, based on the publication by Boogaard and Van Sittert (1995). They concluded that the excretion of S-phenyl mercapturic acid (SPMA) is the most sensitive biomarker of exposure in urine and reported a t1/2; of 9.0±4.5 h or urinary elimination of SPMA. Further, the following regression equation was reported for an 8-h TWA occupational exposure (DFG, 2008):

Using this equation an exposure to the 8-h AEGL-2 of 200 p.p.m. corresponds to an SPMA concentration of ≈9,000 μg/g creatinine. For the purpose of conversion, 1 mg/g creatinine is assumed to be equal to 1 mg/l. With a 95 percentile value (P95) for the background of SPMA in urine of 7.3 μg/l (Scheepers, 2009), the critical longest post-exposure sampling time (ts) can be calculated as:

Completing Eq. (5) with the data for benzene gives ts ≈93 h. This means that urine should be collected within approximately 4 days after the incident. Assuming that the estimated exposure during the incident described in the case study was approximately 300 p.p.m. for 8 h, not much more time is available to organize urine sampling (ts ≈98 h).

It is noted that different relationships between benzene concentrations in air and urinary SPMA concentrations have been published (ACGIH, 2001). For instance, based on the relationship published by Ghittori et al. (1995) an air concentration of 200 p.p.m. benzene would lead to a calculated SPMA concentration of 2,006 μg/g creatinine, which would give an estimation of ts≈73 h (3 days).

Zero-order elimination

For those biomarkers that follow zero-order kinetics, such as protein adducts encapsulated in circulating blood cells, another equation should be used:

In this equation, α is the slope of the function describing the loss of adduct per day and is dependent on the lifespan of hemoglobin, which is equal to the lifespan of the erythrocyte (ter; Törnqvist et al., 2002). This lifespan is 126 days, and hence:

If the adduct is stable, the lifespan of the erythrocyte is equal to the lifespan of the adduct. The lifespan of the adduct is twofold the biomarker half-life:

For t=ts, Eq. (6) can be rewritten as:

Using Eq. (8) this is equivalent to:

At t=ts, C ts becomes equal to LOQ (or P95 if the background level of the biomarker is higher than the LOQ). If LOQ (or P95) ≪ Ce Eq. (10) can be simplified to:

In chemical incidents this simplification can often be used because of the extremely high exposure relative to the value of the LOQ or the background biomarker level.

Case 2: acrylonitrile

For acrylonitrile the parameter estimates are taken from an incident described by Bader and Wrbitzky (2006). They reported an effective half-life for the adduct of ∼75 days in humans. The researchers suggest that this half-life is longer than the half-life of hemoglobin (63 days) because of a depot of circulating reactive intermediates that leads to an extended internal exposure relative to the duration of external exposure.

For the case study of the spill of acrylonitrile in Amersfoort, it is assumed that exposure occurs at or around the 1-h AEGL-2 of 58 p.p.m. An established linear relationship between the ambient air concentration and the level of globine adducts (DFG, 2008) is used to estimate the cyanoethylvaline adduct level by extrapolation from this relationship with linear equation:

This yields an adduct level Ce of 8,142 μg/l blood. With a value of LOQ of 0.05 μg/l, Eq. (10) can be used as 0.05 ≪ 8,142. This does not change even if a background of this adduct is assumed in smokers that exceeds the LOQ by a factor of 40 (Scheepers, 2009).

The value for ts is estimated to be 150 days.

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Scheepers, P., Bos, P., Konings, J. et al. Application of biological monitoring for exposure assessment following chemical incidents: A procedure for decision making. J Expo Sci Environ Epidemiol 21, 247–261 (2011). https://doi.org/10.1038/jes.2010.4

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