* Department of Environmental and Occupational Health, Faculty of Medicine, Université de Montréal, P.O. Box 6128, Main Station, Montréal, Québec, Canada, H3C 3J7;
Institut Universitaire romand de Santé au Travail, rue du Bugnon 19, CH-1005, Lausanne, Switzerland, and
Département de Mathématiques et de Statistique and Centre de Recherches Mathématiques, Faculté des arts et des sciences, Université de Montréal, P.O. Box 6128, Main Station, Montréal, Québec, Canada, H3C 3J7
Received May 10, 2001; accepted August 28, 2001
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ABSTRACT |
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Key Words: methanol; formaldehyde; formate; toxicokinetics; modeling; animals; humans.
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INTRODUCTION |
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The toxic effects of acute exposures to high methanol doses in humans are well documented (Liesivuori and Savolainen, 1991; Røe, 1982
; Tephly and McMartin, 1984
; U.S. DHHS, 1993). Neurological effects, such as the initial transient depression of the central nervous system, have generally been reported at blood concentrations of methanol above 6 mmol/l (U.S. DHHS, 1993). However, the severe toxic effects are usually associated with the production and accumulation of formic acid, which causes metabolic acidosis and visual impairment that can lead to blindness and death at blood concentrations of methanol above 31 mmol/l (Røe, 1982
; Tephly and McMartin, 1984
; U.S. DHHS, 1993).
Although the acute toxic effects of methanol in humans are well documented, little is known about the chronic effects of low exposure doses, which are of interest in view of the potential use of methanol as an engine fuel and current use as a solvent and chemical intermediate. Gestational exposure studies in pregnant rodents (mice and rats) have also shown that high methanol inhalation exposures (5000 or 10,000 ppm and more, 7 h/day during days 6 or 7 to 15 of gestation) can induce birth defects (Bolon et al., 1993; IPCS, 1997
; Nelson et al., 1985
).
The potential deleterious effects of methanol have prompted extensive research on its uptake and disposition in animals and humans. This has led to the findings that pulmonary absorption of methanol is very rapid and absorption fraction ranges from about 60 to 85% depending on the species (Dorman et al., 1994; Fisher et al., 2000
; Horton et al., 1992
). Due to the high water solubility of methanol, the distribution of absorbed methanol in the tissues of the body is a function of their relative water content (Sejersted et al., 1983
). Animal studies have reported that systemic methanol is eliminated mainly by metabolism (70 to 97% of absorbed dose) and only a small fraction is eliminated as unchanged methanol in urine and in the expired air (< 34%) (Dorman et al., 1994
; Horton et al., 1992
).
Systemic methanol is extensively metabolized by liver alcohol dehydrogenase and catalase-peroxidase enzymes to formaldehyde, which is in turn rapidly oxidized to formic acid by formaldehyde dehydrogenase enzymes (Goodman and Tephly, 1968; Heck et al., 1983
; Røe, 1982
; Tephly and McMartin, 1984
). Under physiological conditions, formic acid dissociates to formate and hydrogen ions. Current evidence indicates that, in rodents, methanol is converted mainly by the catalase-peroxidase system whereas monkeys and humans metabolize methanol mainly through the alcohol dehydrogenase system (Goodman and Tephly, 1968
; Tephly and McMartin, 1984
). Formaldehyde, as it is highly reactive, forms relatively stable adducts with cellular constituents (Heck et al., 1983
; Røe, 1982
). It can also enter, directly or after oxidation to formate, the tetrahydrofolic-acid-dependent one-carbon pathway to become the building block of many synthetic pathways (Røe, 1982
; Tephly and McMartin, 1984
).
The detoxification of formate occurs mainly by a tetrahydrofolate-dependent multistep pathway to carbon dioxide (CO2) (McMartin et al., 1977; Palese and Tephly, 1975
). A small percentage of body formate is also eliminated directly in the urine (Dorman et al., 1994
; Horton et al., 1992
). Marked species differences in methanol toxicity and metabolism have been reported. Primates and humans appear to be more susceptible to the acute toxicity of methanol than rodents (Tephly and McMartin, 1984
). This has been mainly attributed to the slower metabolism and elimination rate of formate in larger species (Tephly and McMartin, 1984
).
Based on the available toxicokinetic data of methanol in rats, mice, monkeys, and humans, toxicokinetic processes were described in the past using classic 1 to 3 compartmental models with saturable elimination (Batterman et al., 1998; Damian and Raabe, 1996
; Dorman et al., 1994
; Nihlén and Droz, 2000
; Pollack and Brouwer, 1996
; Pollack et al., 1993
; Ward et al., 1995
; Ward and Pollack, 1996
). Physiologically based pharmacokinetic (PBPK) models for methanol in animals and humans were also developed (Fisher et al., 2000
; Horton et al., 1992
; Perkins et al., 1995
; Ward et al., 1997
).
Recently, a different type of multicompartment modeling approach has been developed to describe the disposition kinetics of polychlorinated dibenzo-dioxins and furans (PCDD and PCDFs) (Carrier et al., 1995a,b
), azinphosmethyl and its alkylphosphate metabolites (Carrier and Brunet, 1999
), and methyl mercury and its inorganic metabolites (Carrier et al., 2001a
,b
). This type of biologically based dynamic model is a refinement of classic compartment models, but is closer to biological processes and enables simulations for a variety of exposure scenarios in different species. This heuristic approach allows essential characteristics of intercompartmental transfer processes to be captured using a minimum of parameters and without the need for extensive knowledge of all the physiological processes. The ultimate goal of this approach is to develop a robust human toxicokinetic model based on human data, thus avoiding as much as possible uncertainties associated with animal to human extrapolations.
The objective of the present study was to develop and validate such a biologically based dynamic model to describe the time evolution of methanol and its metabolites in the whole body, and in accessible biological matrices (blood, urine, and expired air), and allow links to be made between the different compartments. This model is constructed by establishing the overall biological determinants of methanol disposition in animals and humans, taking into account the different time-scales involved in the biological processes. The model parameters specific to the species of interest are then determined from direct fits to the in vivo time course data of methanol and its metabolites in blood and excreta (urine and expired air), available in the published literature.
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METHOD AND MODEL PRESENTATION |
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Conceptual and functional representation.
The disposition kinetics of methanol and its metabolites following exposure to methanol was modeled using a multicompartment dynamic system, described mathematically by a system of coupled differential equations. The model conceptual and functional representation is depicted in Figure 1. It aims to be sufficiently detailed to describe the available in vivo data provided by Horton et al. (1992) on the disposition kinetics of methanol and its metabolites in rats. It was then verified that it described equally well the monkey and human kinetic behavior (Dorman et al., 1994
; Osterloh et al., 1996
; Sedivec et al., 1981
).
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The respiratory tract was further represented as a separate compartment since it is the route of entry of inhaled methanol. Excretion compartments were the methanol in the exhaled air, the urinary methanol, the urinary formic acid, the CO2 in the exhaled air, and the excreted unobserved metabolites.
The dynamic of intercompartment exchanges was then described mathematically by a mass balance differential equation system (see Appendix). Essentially, the rates of change in the amounts of methanol and its metabolites in a given compartment were described as the difference between compartment rates of uptake and loss. (Symbols used in the functional representation of the model are presented in Table 1.) Solving numerically the system of differential equations yielded the time courses of methanol and its metabolites in the different compartments.
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Determination of the parameters.
Unknown parameters were estimated individually from a statistical best-fit to the experimental data specific to the species of interest, by using the explicit solutions of subsystems of differential equations when possible (see Appendix). A professional edition of a MathCad software was used for this purpose (MathSoft Inc., Cambridge, MA).
Rat parameters.
Parameters to be determined were the intercompartment transfer rate coefficients and metabolism rate constants. Data of Horton et al. (1992) in male Fischer-344 rats exposed to a single iv dose of 100 mg per kg of body weight of 14C-methanol (n = 4) were used to determine the rat parameters. Blood concentration-time profiles (expressed in mg/l) and cumulative urinary excretion time courses of 14C-methanol and 14C-formate (expressed in µmol) were determined by these authors as well as the cumulative exhalation time courses of 14C-methanol and 14CO2 (expressed in µmol).
In the current study, for the fitting of experimental data and to determine parameters, all the experimental values were converted to burdens expressed in moles. It was then verified that the mass balance was maintained at all time points. Also, reported blood concentration values were converted to whole body burdens by multiplication by the apparent volume of distribution (Vd). In rats, the apparent volume of distribution of methanol (VdMeOH) was determined so that the initial experimental concentration of methanol in blood at time t = 5 min, when converted in terms of burden, gives the iv dose (700 µmol) reported by Horton et al. (1992).
Monkey parameters.
To adapt the model to monkey data, only the values of the intercompartment transfer rates and metabolism constants needed to be modified. Using the same approach as in rats, transfer parameters values of the general model solutions were estimated individually by best-fits, using MathCad, to the available experimental data of Dorman et al. (1994). These authors exposed 4 adult female cynomolgus monkeys (Macaca fascicularis, 35.5 kg) by inhalation to 900 ppm of 14C-methanol for 2 h. Blood concentration-time profiles of 14C-methanol and 14C-formate (expressed in µmol/l) were determined as well as the cumulative urinary excretion of 14C-methanol and 14C-formate 48-h postexposure (expressed in µmol). The time courses of 14C-methanol and 14CO2 exhalation rates (µmol/min) were also established. For the determination of the parameter values, the latter rates were converted to cumulative excretion.
The pulmonary ventilation rate of female cynomolgus monkeys used in the model was that reported by Dorman et al. (1994), that is on average 33 l/h or 0.56 l/min (equivalent to 0.033 m3/h or 0.8 m3/day).
In monkeys, the apparent volume of distribution of methanol was calculated by best-fit of the following equation to the data observed during the constant inhalation built up of methanol blood concentration (B(t)):
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Human parameters.
When possible, the constants were determined using the available human data. This includes the pulmonary absorption fraction of methanol, the pulmonary ventilation rate, the apparent volume of distribution of methanol, the metabolism rate constant kmet of whole body methanol to formaldehyde, and the transfer rate constant km of whole body methanol to urine. The other constant parameters were left as determined in monkeys, which are considered as good surrogates to humans for the study of methanol kinetics.
Pulmonary absorption fraction of methanol used in the model adapted to humans was that reported by Sedivec et al. (1981). The human value was nonetheless close to that determined in rats and monkeys. Human pulmonary ventilation rate used in the model was that reported by Sedivec et al. (1981), that is on average 10.8 l/min. The apparent volume of distribution of methanol was that reported in the literature, hence, corresponds to the volume of human body fluids (liters), expressed per kilogram of body weight. This value is about the same as that determined using the experimental monkey data.
The constant parameter kmet was determined from a best-fit to the blood concentration-time profile of methanol in human volunteers exposed to 200 ppm of methanol vapors for 4 h, as determined by Osterloh et al. (1996). The km value was determined by adjustment to the data of Sedivec et al. (1981) on the urinary excretion time course curves of methanol in volunteers during and following an 8-h inhalation exposure to 300 mg/m3 of methanol vapors.
The experimental data of Sedivec et al. (1981) on the time evolution of urinary methanol concentrations were converted to cumulative urinary excretion of methanol (in µmol) by considering an average time-dependent fraction of a daily urinary excretion of 1.5 l (Knuiman et al., 1986).
Model simulation.
Once the parameters were determined individually by statistical fits to the experimental data, mathematical resolution of the complete model, as represented by the system of differential equations, was performed by the numerical Runge-Kutta method. Model resolution and simulations were also conducted using Mathcad software. This allows prediction of the time evolution of methanol and its metabolites in the different model compartments. In the model, the exposure dose was converted in µmoles for both the iv and inhalation exposures. Thus, whole body burdens and amounts excreted in urine and in the exhaled air are first expressed in µmoles.
In order to simulate the blood concentrations of methanol or formate as a function of time, the amounts in the whole body predicted by the model were simply divided by the respective apparent volume of distribution. For rats and monkeys, the apparent volume of distribution of formate (VdFA) was estimated using a conservation of mass equation for formate burden, and by a best-fit to the observed time course of experimental blood concentration values of formate. For monkeys, this amounts to 6 times the apparent volume of distribution of methanol. For humans, the same multiple was used.
To simulate the concentration-time profile of methanol in urine, predicted excretion rates (dM(t)/dt = km x X(t), expressed in µmol/min) were divided by the urinary flow rate (l/min). To simulate the concentration-time profile of methanol in the exhaled air, predicted exhalation rates (dE(t)/dt = kre x L(t) + kex x X(t), expressed in µmol/min) were divided by the pulmonary ventilation rate (m3/min).
Simulations of exposure scenarios, where continuous or intermittent doses are administered through time, were performed by introducing a nonhomogenous term, g(t), describing these time varying inputs (see Appendix). Simulations can also be conducted for different routes of exposure (iv, inhalation).
Model Validation
The model developed using the previously mentioned data was validated using a new set of experimental data. This includes the kinetic time profiles presented in the inhalation studies of Horton et al. (1992) in rats and monkeys and Batterman et al. (1998) in human volunteers. Also, some human data of Sedivec et al. (1981) not used in the development of the model served to validate the model.
Validation using inhalation data of Horton et al. (1992) in rats.
The model developed using the iv data of Horton et al. (1992) in rats was validated with the inhalation data of the same authors, on the blood concentration-time profile of methanol during and following 6-h inhalation exposures to 200, 1200, and 2000 ppm of methanol in male Fischer-344 rats (n = 4 per group).
For those simulations, the average pulmonary ventilation rate used was 40 ml/min (equivalent to 0.0021 m3/h or 0.051 m3/day) for the 200 ppm dose, 40 ml/min (equivalent to 0.0024 m3/h or 0.058 m3/day) for the 1200 ppm dose, and 60 ml/min (equivalent to 0.0033 m3/h or 0.080 m3/day) for the 2000 ppm dose to obtain the best-fit to the experimental data as compared to the average value of 3.04 l/h or 50 ml/min (equivalent to 0.0030 m3/h or 0.073 m3/day) reported by Horton et al. (1992).
Validation using inhalation data of Horton et al. (1992) in monkeys.
The model adapted to the monkey data of Dorman et al. (1996) was validated using the data of Horton et al. (1992) on the blood concentration-time profile of methanol in 3 young adult male rhesus monkeys (Macaca mulatta, 57 kg) exposed to methanol vapor concentrations of 200, 1200, or 2000 ppm for 6 h. For these simulations, the average pulmonary ventilation rate was that reported by Horton et al. (1992), that is 48.9 l/h or 0.81 l/min (equivalent to 0.049 m3/h or 1.2 m3/day).
Validation using inhalation data of Sedivec et al. (1981) and Batterman et al. (1998) in humans.
The data of Sedivec et al. (1981) on the urinary excretion time course curves of methanol in volunteers during and following 8-h inhalation exposures to 102 and 205 mg/m3 of methanol vapors were used in the validation process of the model for humans.
The model adapted to human data was also validated using the data of Batterman et al. (1998) on the time-dependent disposition of methanol in blood, urine, and breath of volunteers exposed to methanol vapor concentration of 800 ppm for periods of 0.5, 1, and 2 h.
Batterman et al. (1998) presented their data as urinary and exhaled concentration-time profiles (expressed in mg/l and ppm, respectively). Although in this article the time courses of methanol cumulative excretion in urine and exhaled air are usually presented to insure mass balance conservation, it was also verified that the model gave a good prediction of the overall concentration-time profiles of methanol in urine and exhaled air (data not shown). To obtain a good fit on both the concentration values and cumulative burdens, a time-dependent fraction of a daily urinary excretion of 2.4 l for the 30 min and 2 h exposures and of 2.7 l for the 1 h exposure had to be considered. It has been reported that the daily personal urine volume may commonly vary from 0.6 l to more than 2.5 l (Knuiman et al., 1986). The average pulmonary ventilation rate used was 11.3, 8.4, and 10.8 l/min for the 30 min, 1 h, and 2 h exposures, respectively, to obtain a best-fit to the exhalation data. These latter rates are in the value range reported by Sedivec et al. (1981; average [range]: 10.8 [8.413.8] l/min).
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RESULTS |
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The model predicts that methanol elimination from the whole body is quite rapid (mean elimination half-life of 1.3 h) and that, on average, only 0.01% of methanol remains in the unchanged form 18 h following iv injection of 100 mg/kg of 14C-methanol in rats. Peak levels of free formaldehyde in the whole body are reached 0.5 h postdosing, at which time formaldehyde burden represents on average 3.2% of the injected dose. Virtually no free formaldehyde remains in the body 18 h postexposure. The metabolism of methanol to formaldehyde (kmet) is predicted to be the rate limiting step in the whole body elimination kinetics of free formaldehyde. Indeed, the biotransformation of formaldehyde to its by-products is estimated to be very rapid (kform + koth being very large) compared to methanol metabolism to formaldehyde (kmet), as apparent when comparing reports of McMartin et al. (1979) and Horton et al. (1992).
On the other hand, according to model predictions, peak levels of unbound formate in the whole body are reached only 33.5 h postexposure where average formate burden represents 20.1% of injected 14C-methanol. Eighteen h postexposure, on average 0.5% of the dose remains in the body as free formate. Initial build-up of unbound formate in the body prior to attrition is dependent on the fact that the metabolism rate constant of formaldehyde to formate (kform) is very rapid (average half-life of about 10 min) compared to the major elimination route of formate, the metabolism rate to CO2 and subsequent exhalation (kCO2), for which a mean half-life of 2.2 h can be calculated. Since the urinary excretion of formate is negligible compared to CO2 exhalation, the former contributes only marginally to the whole body time course of formate.
In fact, the model predicts that on average 48.8% of the 14C-methanol iv dose is eliminated as exhaled CO2 as compared to 1.7% as urinary formate, which is congruent with the experimental results of Horton et al. (1992). In comparison, it is estimated from the model that on average 0.8% of the dose is excreted as unchanged methanol in the urine and 2.4% of body methanol is exhaled unchanged again in accordance with the experimental data of Horton et al. (1992).
Model Validation Using the Inhalation Data of Horton et al. (1992) in Fischer-344 Rats
With the parameter values determined using the iv data of Horton et al. (1992), the model was applied to another set of data from the same authors on the blood concentration-time profiles of methanol during and following 6-h inhalation exposures to 200, 1200, and 2000 ppm of methanol in male Fischer-344 rats. It gave a good prediction of the time-course curves for the 2 lowest doses but underestimated the blood concentrations for the 2000 ppm dose (data not shown).
Thus, a new value of the saturation constant Km was estimated from a statistical best-fit on the blood concentration-time profile data of Horton et al. (1992) in male Fischer-344 rats exposed by inhalation to 2000 ppm of methanol vapors for 6 h (Km-Inh) (see Table 2). This Km-Inh value was about 3 times smaller than that determined with the iv data (on average 235 µmol). Thus, after inhalation exposure to 2000 ppm, saturation of methanol metabolism appears to occur at a lower body burden. With this Km-Inh value, a Vmax of 125 µmol/h was calculated. Using this newly determined Km constant for an inhalation exposure, the proposed model provided a close approximation to the data of Horton et al. (1992) on the blood concentration-time profiles of methanol in male Fischer-344 rats exposed to vapor concentrations of 200, 1200, and 2000 ppm of methanol for 6 h (Fig. 4
).
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Further comparison of monkey and rat parameter values shows that the estimated monkey metabolism rate constant kform of whole body formaldehyde to formate was 2.0 times lower than that of rats. This was also the case for exhalation rate constant kex of absorbed methanol (1.8 times). The monkey kCO2 value, which represents a combined metabolism rate constant of whole body formate to CO2 and transfer rate constant of CO2 to the exhaled air, was estimated to be 2.6 times higher than in rats. As observed with the rat data of Horton et al. (1992), no saturation of formaldehyde or formate metabolism was apparent from the data of Dorman et al. (1994).
It is also noteworthy that the estimated monkey transfer rate constant ku of whole body formate to urine was 5.4 times lower than in rats and the monkey transfer rate constant km of whole body methanol to urine was 12.8 times smaller than that obtained for rats. The estimated monkey apparent volume of distribution of methanol and formate, expressed in liters per kilogram of body weight, were only slightly lower than those of the rats (1.2 and 1.4 times, respectively).
With the parameter values described in Table 2, Figure 5
shows that the model provides a close approximation to the data obtained by Dorman et al. (1994) on the blood concentration-time profiles of methanol and formate as well as the time dependent variations in methanol and CO2 exhalation rates over the 8-h period following the beginning of a 2-h inhalation exposure to 900 ppm of 14C-methanol in adult female cynomolgus monkeys. Although the corresponding detailed urinary excretion profiles of methanol and formate were not depicted by Dorman et al. (1994), cumulative excretion of methanol and formate in urine was reported. The model succeeded in reproducing closely these values (0.43 µmol predicted as compared to 0.41 µmol observed on average for urinary methanol, and 1.12 µmol predicted as compared to 1.15 µmol observed on average for urinary formate).
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Model Adapted to the Human Data of Osterloh et al. (1996) and Sedivec et al. (1981)
The parameter values estimated by fitting the model to the observed data of Osterloh et al. (1996) and Sedivec et al. (1981) on the disposition of methanol and its metabolites in humans are presented in Table 2. The estimated value of kmet was in the same range as that determined in animals. The km value was estimated to be close to that obtained in rats (1.5 times lower) but 8.3 times higher than that of monkeys.
Figure 7 shows that the model simulates correctly the data obtained by Osterloh et al. (1996) on the concentration-time course of blood methanol in human volunteers exposed by inhalation to 200 ppm of methanol for 4 h. The model included a constant background whole body methanol burden of 2133 µmol, which corresponds to the mean blood concentration of 1.5 mg/l of methanol measured by Osterloh et al. (1996) in control subjects at the end of an 8-h frequent blood sampling period. In accordance with the experimental data of Osterloh et al. (1996), the model predicts a log-linear elimination of blood methanol over the 4-h sampling period following exposure (data not shown), indicating the absence of saturation of methanol metabolism for the 4-h inhalation exposure at 200 ppm.
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Thus, at the end of a 5-day continuous inhalation exposure to 200 ppm of methanol vapors, predicted methanol concentrations in blood and urine were 5 to 11 times greater than reported mean background values of unexposed subjects (1 mg/l in blood and 0.73 mg/l in urine) (Osterloh et al., 1996; Sedivec et al., 1981
). On the other hand, predicted concentrations of blood formate and urinary formic acid in humans (0.16 and 1.5 mg/l, respectively), although in accordance with the experimental data from methanol exposures in primates and humans, were well below mean background values of unexposed subjects (4.910.3 mg/l in blood and 6.313 mg/l in urine) reported by various authors (Baumann and Angerer, 1979
; D'Alessandro et al., 1994
; Heinrich and Angerer, 1982
; Lee et al., 1992
; Osterloh et al., 1996
).
The model simulations suggest that an 8-h inhalation exposure of at least 500 to 2000 ppm, without physical activities, would be necessary for blood formate and urinary formic acid concentrations to reach reported mean background values. The exact exposure levels necessary depend on the values assumed for the absorption fraction, the pulmonary ventilation rate, and the daily urinary excretion rate. There are considerable variations in the literature for these parameters.
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DISCUSSION |
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The model showed that the kinetics of systemic methanol were dependent on the pulmonary uptake and on the metabolism of methanol to formaldehyde. The pulmonary absorption fraction and ventilation rate were the only model parameters that needed to be modified within a species to provide a good prediction of all the data sets. These predicted parameters were, however, in the value range reported in the published literature (Dorman et al., 1994; Fisher et al., 2000
; Horton et al., 1992
; Sedivec et al., 1981
). The pulmonary absorption fraction did not appear to be influenced by the exposure level or duration nor by the pulmonary ventilation rate, as observed previously by Sedivec et al. (1981) and Medinsky et al. (1997).
For all the other parameters, a single set of values for a given species and strain was found to provide a close approximation to the available kinetic time profile data. In particular, a single average value for the metabolism rate constants can be used in the model for a given exposure route. In accordance with the published animal data (Dorman et al., 1994; Horton et al., 1992
), the model predicts that absorbed methanol is eliminated mainly by metabolism to formaldehyde and that only a minor fraction of the exposure dose is eliminated as unchanged methanol in urine.
On the other hand, from the rat data of Horton et al. (1992), differences in the saturation of methanol metabolism were observed depending on the exposure route. Indeed, in the rat model, a same value for the metabolism rate constant of whole body methanol to formaldehyde, kmet, was found to provide a close approximation to the data of Horton et al. (1992) on the blood concentration-time profiles of methanol after iv and inhalation exposures to methanol in Fischer-344 rats. However, the Km value determined using the inhalation data was 3 times smaller than that obtained using the iv data. Although methanol has been reported to be metabolized mainly in the liver, pulmonary metabolism is also likely to occur. Indeed, the catalase-peroxidase system responsible for a major fraction of methanol metabolism in rats is widely distributed in mammalian tissues (Housset, 1986; Morikawa and Harada, 1969
; Sugata et al., 1979
). It is, in particular, present in the membranes of the upper respiratory tract, the main site of pulmonary absorption of methanol (Perkins et al., 1996
). Of course, given that the Km parameters were estimated from mean blood concentration data without taking into account interindividual variations, it cannot be excluded that there is no significant difference between the 2 route-specific Km values.
It should be remembered that, only in the case of methanol metabolism to formaldehyde was a saturation constant necessary. As mentioned previously, for the exposure dose range of the studies on which the model is based, no saturation of formate or CO2 metabolism was apparent (Dorman et al., 1994; Horton et al., 1992
; Osterloh et al., 1996
; Sedivec et al., 1981
). Though the saturation of formate metabolism has been reported after very high iv doses of sodium formate in rats (164, 328, and 492 mg/kg; Damian and Raabe, 1996
) and appeared to occur in a case of methanol poisoning in a human subject (Jacobsen et al., 1988
), under inhalation exposures levels in occupational and general environments, it is unlikely to occur.
According to model predictions, congruent with the data in the literature (Dorman et al., 1994; Horton et al., 1992
), a certain fraction of formaldehyde is readily oxidized to formate, a major fraction of which is rapidly converted to CO2 and exhaled, whereas a small fraction is excreted as formic acid in urine. However, fits to the available data in rats and monkeys of Horton et al. (1992) and Dorman et al. (1994) show that, once formed, a substantial fraction of formaldehyde is converted to unobserved forms. This pathway contributes to a long-term unobserved compartment. The latter, most plausibly, represents either the formaldehyde that (directly or after oxidation to formate) binds to various endogenous molecules (Heck et al., 1983
; Røe, 1982
) or is incorporated in the tetrahydrofolic-acid-dependent one-carbon pathway to become the building block of a number of synthetic pathways (Røe, 1982
; Tephly and McMartin, 1984
). That substantial amounts of methanol metabolites or by-products are retained for a long time is verified by Horton et al. (1992) who estimated that 18 h following an iv injection of 100 mg/kg of 14C-methanol in male Fischer-344 rats, only 57% of the dose was eliminated from the body. From the data of Dorman et al. (1994) and Medinsky et al. (1997), it can further be calculated that 48 h following the start of a 2-h inhalation exposure to 900 ppm of 14C-methanol vapors in female cynomolgus monkeys, only 23% of the absorbed 14C-methanol was eliminated from the body. These findings are corroborated by the data of Heck et al. (1983) showing that 40% of a 14C-formaldehyde inhalation dose remained in the body 70 h postexposure.
In the present study, the model proposed rests on acute exposure data, where the time profiles of methanol and its metabolites were determined only over short time periods (a maximum of 6 h of exposure and a maximum of 48 h postexposure). This does not allow observation of the slow release from the long-term components.
It is to be noted that most of the published studies on the detailed disposition kinetics of methanol regard controlled short-term (iv injection or continuous inhalation exposure over a few hours) methanol exposures in rats, primates, and humans (Batterman et al., 1998; Damian and Raabe, 1996
; Dorman et al., 1994
; Ferry et al., 1980
; Fisher et al., 2000
; Franzblau et al., 1995
; Horton et al., 1992
; Jacobsen et al., 1988
; Osterloh et al., 1996
; Pollack et al., 1993
; Sedivec et al., 1981
; Ward et al., 1995
; Ward and Pollack, 1996
). Experimental studies on the detailed time profiles following controlled repeated exposures to methanol are lacking. Data on methanol and formate concentrations in spot blood and urine samples of chronically exposed workers (Baumann and Angerer, 1979
; Kawai et al., 1991
; Yasugi et al., 1992
) are available but uncertainties regarding the exposure dose and concomitant exposure to other chemicals limit their use in the elaboration of a kinetic model.
With regard to the apparent volume of distribution of methanol, which was calculated in the current study using classic approaches (see Method and Model Presentation), it was expected that its value would correspond approximately to the whole body water content. The slightly larger weight adjusted volume of distribution of methanol calculated in rats (0.92 l/kg of body weight) as compared to monkeys (0.77 l/kg of body weight) can be explained by the smaller adipose tissue fraction of body weight in rats.
As for the apparent volume of distribution of formate determined in this study, the weight adjusted values calculated in rats and monkeys were in the same range, although slightly higher in rats than in monkeys (6.4 and 4.6 l/kg of body weight, respectively). However, the volume of distribution of formate was larger than that of methanol, which strongly suggests that formate distributes in body constituents other than water, such as proteins. The closeness of our simulations to the available experimental data on the time course of formate blood concentrations is consistent with the volume of distribution concept (i.e., rapid exchanges between the nonblood pool of formate and blood formate).
Species Differences in the Kinetics of Methanol and Its Metabolites
Critical biological determinants of species differences in the disposition of methanol and its metabolites were determined from in vivo data from several studies (Batterman et al., 1998; Fisher et al., 2000
; Horton et al., 1992
; Sedivec et al., 1981
). In agreement with their findings, the model predicts that the average pulmonary absorption fraction fabs of methanol and the metabolism rate constant kmet of whole body methanol to formaldehyde were in the same value range in rats, monkeys, and humans (on average 0.580.82 for fabs and 0.2190.96/h for kmet). However, the saturation of methanol metabolism appeared to occur at a lower exposure dose in rats than in monkeys and humans. Indeed, from the data of Horton et al. (1992) on the blood concentration-time profile of methanol in rats exposed to 2000 ppm of methanol vapors for 6 h, a Km value of 36.6 mg/l of blood and Vmax of 19.4 mg/l/h were estimated in the current study whereas following a similar exposure in monkeys, no saturation of methanol metabolism was apparent. The model also predicts that there is no saturation of methanol metabolism from the data of Batterman et al. (1998) in human volunteers exposed to 800 ppm of methanol vapors for 2 h nor from those of Sedivec et al. (1981) in volunteers exposed to 229 ppm of methanol vapors for 8 h.
Interestingly, a striking species difference in the kinetics was attributed to a metabolism rate constant ratio kform/kfald of whole body formaldehyde to formate twice as high in rats than in monkeys (0.53 vs. 0.26). Thus, in monkeys and plausibly humans, a much larger fraction of body formaldehyde is rapidly converted to unobserved forms rather than passed on to formate and eventually CO2.
Comparison of the Current Model with Others Previously Published
The current biologically based dynamic model can be compared to some of the previously published models. In particular, Horton et al. (1992) developed a PBPK model to describe the kinetics of methanol and its metabolites in rats, monkeys, and humans. Their model was comprised of 4 compartments: liver, kidney, and richly and slowly perfused tissues. As in our model, the metabolism of methanol to formaldehyde was assumed to be the main biological determinant of methanol elimination kinetics. In addition, in both the current model and that published by Horton et al. (1992), not only were the kinetics of methanol in blood, urine, and exhaled air modeled but also the time evolution of formate in blood and urine and of CO2 in the exhaled air. However, in the study of Horton et al. (1992), 2 saturable metabolic pathways for methanol metabolism were considered whereas in our study, even by introducing only 1 metabolism route for methanol, with saturable elimination, the model gave a good prediction of the experimental data. In the PBPK model of Horton et al. (1992), the metabolism of formate and CO2 was also assumed to follow Michaelis Menten kinetics. In our model, as mentioned previously, no saturation constants for these metabolism processes were introduced since fits to the available time course data suggested the absence of saturation of formate and CO2 metabolism in the exposure dose range used in the studies on which the model is based.
Furthermore, conceptual and functional differences between the current model and the PBPK model of Horton et al. (1992) are related to the fact that the current model compartmentalization is dependent on the availability of experimental data on the detailed time course of methanol and its metabolites in blood, tissues, and excreta and on the hierarchy of the time scales for the various biological processes. The main structural difference between our model and that of Horton et al. (1992) concerns our regrouping into a single compartment the methanol body burden whereas Horton et al. (1992) have fragmented the body into several compartments according to the general PBPK structure. In our model, methanol body burden regrouping relies on the fact that methanol distributes uniformly and rapidly in total body water and thus the apparent volume of distribution of methanol corresponds to the total body water content. This allowed us to reduce the number of parameters to be determined to describe the overall model dynamics of methanol. Based on the available data on methanol blood kinetics for the 3 species studied, this regrouping also enabled the determination of species specific parameters by direct fits, without the need for allometric extrapolation. Furthermore, the current model ensures conservation of mass by the introduction of an unobserved metabolite compartment. In the model of Horton et al. (1992), to account for the fraction of the methanol dose that was unobserved experimentally and thus to obtain a good fit to their experimental data on the cumulative exhalation of CO2 in rats exposed to 14C-labeled methanol, the rate of formate metabolism had to be multiplied by 0.6 to correspond to the fraction of the methanol dose eventually excreted as CO2 over the 18-h sample collection period of their study.
More recently, Fisher et al. (2000) published a PBPK model for monkeys to describe the kinetics of methanol. The structure of their PBPK model for methanol was similar to that of Horton et al. (1992) but also accounted for the fractional systemic uptake of inhaled methanol vapors in the lungs. This fractional systemic uptake was also introduced in our model.
Prediction of the Most Useful Biological Indicator of Exposure to Methanol
The biological monitoring of exposure, through the analysis of blood concentrations or urinary and exhaled levels, has become an increasingly popular means of estimating the absorbed dose. This model can be used in conjunction with biological measurements of methanol and formate or formic acid to determine the level of exposure and subsequent build-up in tissues. It can also help to establish the best biomarker of exposure, the sampling strategy for routine monitoring and the significance of measurements at different times.
Since systemic formate is thought to be responsible for a large part of the deleterious effects induced by methanol exposures (Tephly and McMartin, 1984), the measurement of blood formate or urinary formic acid appears interesting a priori for the biological monitoring of exposure to methanol. However, the model shows that background concentrations of formate are much higher than those stemming from fairly high methanol exposures. Indeed, the model, adapted to kinetic data in human volunteers exposed acutely to methanol vapors, predicts that 8-h inhalation exposures ranging from 500 to 2000 ppm are needed to increase blood formate concentrations above reported mean endogenous values of 4.9 to 10.3 mg/l (Baumann and Angerer, 1979
; Lee et al., 1992
; Osterloh et al., 1996
), and for urinary formic acid concentrations to reach the published mean background values of 6.3 to 13 mg/l (Baumann and Angerer, 1979
; D'Alessandro et al., 1994
; Heinrich and Angerer, 1982
). The monkey data of Dorman et al. (1994) show that even after a 2-h inhalation exposure to 900 ppm of 14C-methanol in female cynomolgus monkeys, 14C-formate concentrations in blood were far below normal endogenous values. Likewise, studies in human volunteers acutely exposed to methanol, at the level of 200 ppm, concur to indicate that blood formate and urinary formic acid concentrations remain within the background value range of unexposed subjects (D'Alessandro et al., 1994
; Franzblau et al., 1993
; Lee et al., 1992
; Osterloh et al., 1996
).
Only in the studies of Kawai et al. (1991) and Yasugi et al. (1992) was a significant correlation between the urinary excretion of formic acid and exposure to methanol vapors observed. However, the workers were exposed to airborne concentrations of methanol of up to 4000 ppm over an 8-h workshift.
These findings suggest that it is not justified to monitor concentrations of blood formate or urinary formic acid at methanol exposure levels in the range of or below the airborne threshold limit value of 200 ppm for occupational settings. If toxic effects do occur following low level methanol exposures, the mode of action is not likely to be through the accumulation of formate. As suggested by some reports (Cook et al., 1991; Kingsley and Hirsch, 1954
), it may rather be attributable to methanol itself.
The use of formate as a biomarker of exposure to methanol is further limited by the fact that it is not a specific metabolite of methanol exposure. Also, background concentrations of formate are subject to wide interindividual variations (Baumann and Angerer, 1979; D'Alessandro et al., 1994
; Franzblau et al., 1995
; Heinrich and Angerer, 1982
; Lee et al., 1992
; Osterloh et al., 1996
; Sedivec et al., 1981
). This leaves blood and urinary methanol as the most appropriate biomarkers of absorbed methanol. Since the model relates blood and urinary methanol burdens to the exposure dose and body burdens of metabolites at all time points, it can be of great use in reconstructing past and present exposure levels starting from methanol amounts in blood and urine.
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APPENDIX |
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![]() | ((1)) |
The fraction of absorption through the lungs can be defined as fabs = kabs/(kabs + kre).
![]() | ((2)) |
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Considering the rapid exchange rates between the various internal organs and blood, and thus between the whole body burden and blood, it can be considered that
![]() | ((3)) |
![]() | ((4)) |
![]() | ((5)) |
Kinetics of the Formaldehyde Form
![]() | ((6)) |
The global breakdown rate of formaldehyde, kfald = kform + koth, is very large compared to the subsequent transfer rates {ku and kCO2} because observed formaldehyde levels are very small compared to formate levels. This implies rapid breakdown of formaldehyde compared to formate elimination rates. The rate of formaldehyde breakdown, kfald, was given the value reported by McMartin et al. (1979) in cynomolgus monkeys, corresponding to a half-life of 1.5 min. However, its exact value is not relevant to the model's unfolding, only the ratios kform/kfald and koth/kfald are.
![]() | ((7)) |
![]() | ((8)) |
![]() | ((9)) |
![]() | ((10)) |
![]() | ((11)) |
![]() | ((12)) |
Mass Balance Verification
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NOTES |
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REFERENCES |
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