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Protein markers of body composition in response to growth hormone (GH) treatment in short prepubertal children

Conference paper
Authors Ralph Decker
Björn Andersson
Andreas F M Nierop
Jovanna Dahlgren
Gunnel Hellgren
Kerstin Albertsson-Wikland
Published in Hormone Research Paediatr
Volume 74
Issue (suppl 3)
Pages 103
Publication year 2010
Published at Institute of Clinical Sciences, Department of Pediatrics
Pages 103
Language en
Keywords Proteomics, biomarkers, body composition, lean mass, fat mass, bone mineral content, BMC, LBM, bone mass
Subject categories Clinical pharmacology, Clinical physiology

Abstract

Background Recently our group identified lipoprotein biomarkers able to predict linear growth response to GH treatment in short prepubertal children. Previously, it was also shown that biomarkers identified by a proteomic approach were able to discriminate between good or poor growth responders to GH treatment. Hypothesis We hypothesize that high-throughput proteomics techniques can be used to identify proteins not only to predict longitudinal growth response, but also changes in body composition. Objectives The objectives are to implement newly identified biomarkers in future advanced prediction models to avoid over- and under-treatment with GH and to find surrogate markers for predictors difficult to access, e.g. growth hormone (GH) secretion capacity. Study design 128 short prepubertal children were included in the study receiving GH treatment, of whom 39 were GH-deficient and 89 had idiopathic short stature (ISS). Serum protein expression profiles at study start and after 1 year of GH treatment were analyzed using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). Body composition after 2 years was analyzed by DEXA. Statistics Cross-validated regression and random permutation analyses were performed to identify significant correlations between protein expression patterns and the 2-year changes in body composition during GH treatment. Results In the present study we identified biomarkers able to predict lean mass (from arms and legs) and the decrease in subcutaneous fat mass (from arms and legs) at 2 yrs using a pharmaco-proteomic approach. Apolipoproteins were identified as unique markers of the GH treatment on lean mass and of fat mass (r2 >0.32, p<0.05). Serum amyloid A4, belonging to the apolipoprotein family, was a marker of both muscle and fat mass. Conclusion We show a proteomic approach being suitable to identify biomarkers before start of GH treatment playing a role in lipid transport and lipid metabolism able to predict body composition at 1 and 2 years of GH treatment.

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