Cassandra Smith1, Sarah Voisin2, Ahmed Al Saedi3, Steven Phu3, Tara Brennan-Speranza4, Lewan Parker5, Nir Eynon6, Danielle Hiam2, Xu Yan2, David Scott7, Lauren C Blekkenhorst8, Joshua R Lewis9, Ego Seeman10, Elizabeth Byrnes11, Leon Flicker12, Gustavo Duque3, Bu B Yeap13, Itamar Levinger14. 1. Institute for Health and Sport (iHeS), Victoria University, Melbourne, VIC, Australia; Australian Institute for Musculoskeletal Science (AIMSS), University of Melbourne and Western Health, St Albans, VIC, Australia. 2. Institute for Health and Sport (iHeS), Victoria University, Melbourne, VIC, Australia. 3. Australian Institute for Musculoskeletal Science (AIMSS), University of Melbourne and Western Health, St Albans, VIC, Australia; Department of Medicine-Western Health, Melbourne Medical School, The University of Melbourne, Melbourne, VIC, Australia. 4. Department of Physiology and Bosch Institute for Medical Research, University of Sydney, New South Wales, Australia. 5. Institute for Physical Activity and Nutrition (IPAN), Deakin University, Geelong, VIC, Australia. 6. Institute for Health and Sport (iHeS), Victoria University, Melbourne, VIC, Australia; Murdoch Childrens Research Institute, Melbourne, Australia. 7. Australian Institute for Musculoskeletal Science (AIMSS), University of Melbourne and Western Health, St Albans, VIC, Australia; School of Clinical Sciences at Monash Health, Monash University, Melbourne, VIC, Australia. 8. School of Medical and Health Sciences, Edith Cowan University, Perth, Australia; Medical School, University of Western Australia, Perth, Australia. 9. School of Medical and Health Sciences, Edith Cowan University, Perth, Australia; Medical School, University of Western Australia, Perth, Australia; Centre for Kidney Research, Children's Hospital at Westmead School of Public Health, Sydney Medical School, The University of Sydney, Sydney, Australia. 10. University of Melbourne and the Department of Endocrinology, Austin Health and the Mary Mackillop Institute of Healthy Aging, Australian Catholic University, Melbourne, Australia. 11. Department of Biochemistry, PathWest Laboratory Medicine, Queen Elizabeth II Medical Centre, Perth, Australia. 12. Medical School, University of Western Australia, Perth, Australia; Western Australian Centre for Health & Ageing, University of Western Australia, Perth, Australia. 13. Medical School, University of Western Australia, Perth, Australia; Department of Endocrinology and Diabetes, Fiona Stanley Hospital, Perth, Australia. 14. Institute for Health and Sport (iHeS), Victoria University, Melbourne, VIC, Australia; Australian Institute for Musculoskeletal Science (AIMSS), University of Melbourne and Western Health, St Albans, VIC, Australia; Department of Medicine-Western Health, Melbourne Medical School, The University of Melbourne, Melbourne, VIC, Australia. Electronic address: itamar.levinger@vu.edu.au.
Abstract
PURPOSE: Osteocalcin (OC), an osteoblast-specific secreted protein expressed by mature osteoblasts, is used in clinical practice and in research as a marker of bone turnover. The carboxylated (cOC) and undercarboxylated (ucOC) forms may have a different biological function but age-specific reference ranges for these components are not established. Given the different physiological roles, development of reference ranges may help to identify people at risk for bone disease. METHODS: Blood was collected in the morning after an overnight fast from 236 adult men (18 to 92 years old) free of diabetes, antiresorptive, warfarin or glucocorticoid use. Serum was analyzed for total osteocalcin (tOC) and the ucOC fraction using the hydroxyapatite binding method. cOC, ucOC/tOC and cOC/tOC ratios were calculated. Reference intervals were established by polynomial quantile regression analysis. RESULTS: The normal ranges for young men (≤30 years) were: tOC 17.9-56.8 ng/mL, ucOC 7.1-22.0 ng/mL, cOC 8.51-40.3 ng/mL (2.5th to 97.5th quantiles). Aging was associated with a "U" shaped pattern for tOC, cOC and ucOC levels. ucOC/tOC ratio was higher, while cOC/tOC ratio was lower in men of advanced age. Age explained ∼31%, while body mass index explained ∼4%, of the variance in the ratios. CONCLUSIONS: We have defined normal reference ranges for the OC forms in Australian men and demonstrated that the OC ratios may be better measures, than the absolute values, to identify the age-related changes on OC in men. These ratios may be incorporated into future research and clinical trials, and their associations with prediction of events, such as fracture or diabetes risk, should be determined.
PURPOSE:Osteocalcin (OC), an osteoblast-specific secreted protein expressed by mature osteoblasts, is used in clinical practice and in research as a marker of bone turnover. The carboxylated (cOC) and undercarboxylated (ucOC) forms may have a different biological function but age-specific reference ranges for these components are not established. Given the different physiological roles, development of reference ranges may help to identify people at risk for bone disease. METHODS: Blood was collected in the morning after an overnight fast from 236 adult men (18 to 92 years old) free of diabetes, antiresorptive, warfarin or glucocorticoid use. Serum was analyzed for total osteocalcin (tOC) and the ucOC fraction using the hydroxyapatite binding method. cOC, ucOC/tOC and cOC/tOC ratios were calculated. Reference intervals were established by polynomial quantile regression analysis. RESULTS: The normal ranges for young men (≤30 years) were: tOC 17.9-56.8 ng/mL, ucOC 7.1-22.0 ng/mL, cOC 8.51-40.3 ng/mL (2.5th to 97.5th quantiles). Aging was associated with a "U" shaped pattern for tOC, cOC and ucOC levels. ucOC/tOC ratio was higher, while cOC/tOC ratio was lower in men of advanced age. Age explained ∼31%, while body mass index explained ∼4%, of the variance in the ratios. CONCLUSIONS: We have defined normal reference ranges for the OC forms in Australian men and demonstrated that the OC ratios may be better measures, than the absolute values, to identify the age-related changes on OC in men. These ratios may be incorporated into future research and clinical trials, and their associations with prediction of events, such as fracture or diabetes risk, should be determined.
Authors: Alexander Tacey; Cassandra Smith; Mary N Woessner; Paul Chubb; Christopher Neil; Gustavo Duque; Alan Hayes; Anthony Zulli; Itamar Levinger Journal: PLoS One Date: 2020-11-25 Impact factor: 3.240
Authors: Anna L Höving; Kazuko E Schmidt; Barbara Kaltschmidt; Christian Kaltschmidt; Cornelius Knabbe Journal: Int J Mol Sci Date: 2022-08-25 Impact factor: 6.208