de Andrade V Lopes, Mateus M L, Aschner M, Dos Santos Ap Marreilha
Instituto de Investigação do Medicamento, iMed.UL, Faculdade de Farmácia, Universidade de Lisboa, 1649-003 Lisboa, Portugal.
Department of Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, NY 10461, USA.
J Integr OMICS. 2018 Jun;8(1). doi: 10.5584/jiomics.v8i1.216. Epub 2018 Apr 16.
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.
长期职业性接触低水平金属混合物需要对接触工人进行生物监测。然而，单一生物标志物（BM）很少足以确定个体对复杂混合物的接触情况，最近将对同一样本进行多参数分析视为一种首选方法。卟啉是血红素生物合成的中间体，不同金属可在该代谢途径的不同点发挥作用，导致尿卟啉排泄谱发生变化。这项工作的目的是开发一种模型，该模型可用于通过尿卟啉谱在个体基础上识别采矿工作导致的多种金属接触情况。从一家葡萄牙矿业公司获取工人的尿液样本，并将非职业接触组用作对照。通过高效液相色谱法测定尿卟啉、七羧基卟啉、六羧基卟啉、五羧基卟啉、粪卟啉和原卟啉的水平。观察到只有矿工的七羧基卟啉水平与对照组有显著差异（p<0.05）。然而，当通过二元逻辑回归将所有卟啉的浓度合并时，它们区分矿工和对照组的能力高于单独的每种卟啉，如ROC曲线下更大的曲线面积所示。此外，当使用合并的卟啉来计算每个受试者符合职业接触组的概率时，47名个体中有83%在接触类型方面被正确识别。这些结果表明，尿卟啉谱的整合是检测因职业接触矿山金属而表现出生化改变的受试者的一种有前景的工具。
