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Pubertal Changes in Biochemical Markers of Growth
Author(s) -
Giovanni Federico,
Giampiero I. Baroncelli,
Teresa Vanacore,
Lisa B. Fiore,
Giuseppe Saggese
Publication year - 2003
Publication title -
hormone research in paediatrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.816
H-Index - 89
eISSN - 1663-2826
pISSN - 1663-2818
DOI - 10.1159/000071225
Subject(s) - endocrinology , medicine , leptin , n terminal telopeptide , bone remodeling , osteocalcin , bone age , hormone , bone growth , growth hormone , biology , obesity , alkaline phosphatase , biochemistry , enzyme
Puberty is a crucial period of life during which dramatic hormonal changes induce notable modifications in linear growth, bone mass and body composition. These changes are associated with variations in some biochemical parameters such as markers of bone turnover and leptin, which may reflect changes in bone growth and fat mass, respectively. Children with growth hormone (GH) deficiency have reduced concentrations of bone markers, which increase during GH administration, while the levels of leptin decrease. There have been few studies analysing the behaviour of bone markers during puberty in GH-treated GH-deficient patients and no studies analysing the behaviour of leptin. Results from a longitudinal study showed that there was no change in serum osteocalcin, carboxy-terminal propeptide of type I procollagen, and cross-linked carboxy-terminal telopeptide of type I collagen levels during puberty in GH-treated GH-deficient children. Some studies have shown that changes in markers of bone turnover and leptin after short-term GH treatment may predict the growth response (at 6-12 months) to GH administration in GH-deficient children. At present, insufficient data are available for the clinical use of these parameters as markers of growth response during pubertal development and as predictors of long-term growth response to GH treatment in children with GH deficiency. Nevertheless, the use of more and possibly new markers might improve the accuracy of growth prediction models in the future.

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