ABSTRACT
Chronic occupational exposures to low levels of metal mixtures necessitates biomonitoring of exposed workers. However, a single biomarker (BM) is rarely sufficient to ascertain the exposure of an individual to a complex mixture, with multiparameter analysis of the same sample considered recently as a preferred approach. Porphyrins are formed as intermediates of heme biosynthesis and different metals can exert their effects at different points of this metabolic pathway, leading to changed urinary porphyrins excretion profiles. The aim of this work was to develop a model that could serve to identify, on an individual basis, multiple metal exposure resulting from mining work, by using urinary porphyrin profiles. Urine samples of workers were obtained from a Portuguese mining company and a non-occupationally exposed group was used as control. The levels of uro-, hepta-, hexa-, penta-, copro- and protoporphyrins were determined by HPLC. It was observed that only heptaporphyrin levels in miners were significantly (p<0.05) different from controls. However, when the concentrations of all porphyrins were combined by binary logistic regression, their ability to discriminate between miners and controls was higher than each one of the porphyrins alone, as indicated by a greater curve' area under a ROC curve. Moreover, when the combined porphyrins were used to calculate the probability of each subject fit in the occupationally exposed group, 83% of 47 individuals were correctly identified with respect to their type of exposure. These results suggest that the integration of the urinary porphyrin profile is a promising tool for the detection of subjects exhibiting biochemical modifications due to occupational exposure to metals in mines.
