Comparison of results from the semiautomated serum bone alkaline phosphatase isoenzyme assay with the periosteal alkaline phosphatase assay for use in rat models

BACKGROUND: Assessment of bone formation activity is an important component of pharmacologic efficacy and toxicity evaluations for compounds in development for osteoporosis therapies. Antemortem biomarkers of bone formation and remodeling in rodents are uncommon. While the periosteal alkaline phosphatase (ALP) assay is a postmortem and laborious means of testing bone-building activity, the semiautomated ALP isoenzyme assay is an antemortem assay that is performed on an automated chemistry analyzer after 2 simple dilutions of the initial serum sample and a short incubation. OBJECTIVES: The goal of our investigation was to determine if the serum bone ALP (BALP) data obtained from the semiautomated ALP isoenzyme assay had a similar pattern of response when compared with the periosteal ALP (PALP) assay for use in pharmacologic screening in rats. METHODS: Serum and bone tissue samples were obtained from orchidectomized Wistar rats, a model of clinically induced osteoporosis. Subsequent bone formation was initiated via treatment with one of several compounds. In study 1, orchidectomized male rats were given either vehicle, dihydrotestosterone or a testosterone derivative subcutaneously every 4 days for 28 days. In study 2, orchidectomized male rats were given either vehicle or compounds A, B, or C by oral gavage daily for 15 days. Blood and tibias were collected at necropsy. Serum was analyzed for BALP activity using a semiautomated ALP assay. Tibias from the same rats were analyzed for PALP activity. RESULTS: Serum BALP activity paralleled PALP activity within each group when compared with the controls. CONCLUSION: Our data indicate that the semiautomated serum BALP isoenzyme assay may be used as a biomarker of bone-building potential in rat models of osteoporosis. This assay affords many advantages to investigators of musculoskeletal diseases, including the potential to measure multiple data points in a single study.