4.5 Article

Physiologically-Based Toxicokinetic Model for Cadmium Using Markov-Chain Monte Carlo Analysis of Concentrations in Blood, Urine, and Kidney Cortex from Living Kidney Donors

Journal

TOXICOLOGICAL SCIENCES
Volume 141, Issue 2, Pages 365-376

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/toxsci/kfu129

Keywords

cadmium; physiologically-based pharmacokinetics; exposure assessment

Categories

Funding

  1. Sahlgrenska University Hospital [ALF 74580]
  2. Swedish Research Council for Health, Working Life, and Welfare (FORTE) [2010-0216]

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The health effects of low-level chronic exposure to cadmium are increasingly recognized. To improve the risk assessment, it is essential to know the relation between cadmium intake, body burden, and biomarker levels of cadmium. We combined a physiologically-based toxicokinetic (PBTK) model for cadmium with a data set from healthy kidney donors to re-estimate the model parameters and to test the effects of gender and serum ferritin on systemic uptake. Cadmium levels in whole blood, blood plasma, kidney cortex, and urinary excretion from 82 men and women were used to calculate posterior distributions for model parameters using Markov-chain Monte Carlo analysis. For never-and ever-smokers combined, the daily systemic uptake was estimated at 0.0063 mu g cadmium/kg body weight in men, with 35% increased uptake in women and a daily uptake of 1.2 mu g for each pack-year per calendar year of smoking. The rate of urinary excretion from cadmium accumulated in the kidney was estimated at 0.000042 day(-1), corresponding to a half-life of 45 years in the kidneys. We have provided an improved model of cadmium kinetics. As the new parameter estimates derive from a single study with measurements in several compartments in each individual, these new estimates are likely to be more accurate than the previous ones where the data used originated from unrelated data sets. The estimated urinary excretion of cadmium accumulated in the kidneys was much lower than previous estimates, neglecting this finding may result in a marked under-prediction of the true kidney burden.

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