Biomarkers concentration range

Occupational exposure to chemical substances almost invariably involves multiple chemicals. That situation may result in PK interactions, which may affect the relationship between the atmospheric concentration of the parent chemical and the associated biomarker concentration (Viau 2002). For example, such an interaction is known to occur between ethylbenzene and the xylene isomers (Jang et al. 2001). Commercial xylene contains about 20% ethylbenzene, which modifies the slope of the relationship between urinary methylhippuric acid (MHA) and airborne xylene concentrations. That kind of interaction is unlikely at the subparts-per-million exposure concentrations seen in the general population. But because the BEI for MHA was obtained from the relationship observed after exposure to commercial xylene, thereby taking the interaction into account, the slope of the relationship cannot be extrapolated to the subparts-per-million range. Similar PK interactions have been observed for other mixtures but only at concentrations nearing or exceeding the occupational exposure limits (Viau 2002), so it would be a priori reasonable to consider extrapolation of the relationship between biomarker concentrations and those of their parent chemicals. For example, Tardif et al. (1991) demonstrated that, provided inhalation exposure to a mixture of toluene and xylene was kept below their airborne occupational exposure limits, there were no PK interactions between the compounds that affected the linear relationship between airborne parent-chemical exposure and urinary-metabolite concentrations. However, such an interaction was apparent at higher concentrations. 

The reference-range approach is a critical data layer that summarizes the biomonitoring dataset and enables comparisons between segments of the population and times. Although they do not provide information about risk, simple comparisons between an individual s biomarker concentration and the population distribution may be all that is needed to answer key questions about the need for personal action. 

In estimating the range of ingested doses which could have resulted in a given biomarker concentration, there are three main sources of variability errors in model selection, errors in estimation of model parameters, and tme population variability (i.e., heterogeneity). The variability due to the first two sources can be reduced by the collection... 

In addition, the effect of drug administration on the biomarker concentration should be factored in for the standard curve dynamic range. This is often a challenge during the exploratory phase with a novel biomarker because the modulation by a drug candidate may not be known and postdose incurred samples would not be available for the initial tests. 

Fig. 6. Acyclic alkane, hopane and tetracyclic alkane cross plots of end member oils A and B and mixtures of each. Red squares are selected end member oils red circles represent calculated mixtures of oils A and B in 10% increments. Definition of ratios %35ab= 100 x S R C35 homohopane/(S R C34 homohopane + S R C35 homohopane) %24/4= 100 x C24 tetracyclic terpane/(C24 tetracyclic terpane + C23 tricyclic and C25 tricyclic terpane). Note that for the acyclic alkanes which have similar concentration ranges the mixing curve is essentially linear, whereas for the cyclic biomarkers with very different end member concentrations, the mixing curve is distinctively nonlinear. In this illustrative case of course the actual variations in %24/4 are not sensibly interpretable.

In general, for diagnostic applications, the requirements for blood cell removal are extremely onerous, i.e., a 100 % cell removal efficacy. Even a few cells (out of the millions present in a typical sample) have the ability to clog up microchannels and adversely affect sensitive biosensors downstream. The sensitivity of the biosensor and the concentration ranges of the target biomarkers also determine how much the original solution may be diluted. For... 

Biomarkers of atrazine exposure is a developing field (Lu et al. 1998) that merits additional research. For example, concentrations of atrazine in saliva of rats was significantly correlated with rat free atrazine plasma concentrations. About 26% of the atrazine in rats is bound to plasma proteins (and is unavailable for transport from blood to saliva) and is independent of plasma levels of atrazine. Salivary concentrations of atrazine reflect total plasma free atrazine concentration — in the 50 to 250 pg/L range — which may be of toxicological significance (Lu et al. 1998). 

---