The assessment of biomarkers to detect nephrotoxicity using an integrated database.

Groups of industrial workers exposed to heavy metals (cadmium, mercury, and lead) or solvents were studied together with corresponding control groups. The cohorts were collected from several European centers (countries). Eighty-one measurements were carried out on urine, blood, and serum samples and the results of these analyses together with questionnaire information on each individual were entered into a central database using the relational database package Rbase. After the completion of the database construction phase, the data were exported in a format suitable for analysis by the statistical package SAS. The potential value of each test as an indicator of nephrotoxicity was then assessed. Rigorous exclusion criteria were applied which resulted in the elimination of some tests and samples from the dataset. The measurable contributions of smoking, gender, metal exposure, and site were either singly or in combination assessed by biomarkers for nephrotoxicity. The parameters measured included three urinary enzymes, six specific proteins, total protein, two extracellular matrix markers, four prostaglandins and anti-GBM antibodies, and beta 2-microglobulin in serum. The most sensitive renal tests included the urinary enzymes N-acetyl-beta-D-glucosaminidase (NAG) and intestinal alkaline phosphatase (IAP), brush border antigens, and urinary low-molecular-weight proteins. Of the newer tests investigated the prostaglandins were the most promising. Different patterns of biomarker excretion were observed following exposure to lead, cadmium, or mercury. The dataset provides a unique repository of data which could provide the basis of an enlarging source of information on normal human reference ranges and on the effects of exposure to toxins and the use of biomarkers for monitoring nephrotoxicity.