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Title: A proteomic approach combining MS and bioinformatic analysis for the detection and identification of biomarkers of administration of exogenous human growth hormone in humans
Authors: Boateng, Joshua
Kay, Richard G.
Lancashire, Lee
Brown, Pamela
Velloso, Cristiana
Bouloux, Pierre
Teale, Phil
Roberts, Jane
Rees, Robert
Ball, Graham
Harridge, Stephen
Goldspink, Geoffrey
Creaser, Colin S.
Keywords: Bioinformatics
ESI-MS/MS
LC
MALDI
Serum biomarkers
Issue Date: 2009
Publisher: © Wiley VCH Verlag GmbH & Co.
Citation: BOATENG, J. ... et al, 2009. A proteomic approach combining MS and bioinformatic analysis for the detection and identification of biomarkers of administration of exogenous human growth hormone in humans. PROTEOMICS - Clinical Applications, 3 (8), pp. 912 - 922.
Abstract: An integrated MS-based proteomic approach is described that combines MALDI-MS and LC-MS with artificial neural networks for the identification of protein and peptide biomarkers associated with recombinant human growth hormone (rhGH) administration. Serum from exercised males administered with rhGH or placebo was analysed using ELISA to determine insulin-like growth factor-I concentrations. Diluted serum from rhGH- and placebo-treated subjects was analysed for protein biomarkers by MALDI-MS, whereas LC-MS was used to analyse tryptically digested ACN-depleted serum extracts for peptide biomarkers. Ion intensities and m/z values were used as inputs to artificial neural networks to classify samples into rhGH- and placebo-treated groups. Six protein ions (MALDI-MS) correctly classified 96% of samples into their respective groups, with a sensitivity of 91% (20 of 22 rhGH treated) and specificity of 100% (24 of 24 controls). Six peptide ions (LC-MS) were also identified and correctly classified 93% of samples with a sensitivity of 90% (19 of 21 rhGH treated) and a specificity of 95% (20 of 21 controls). The peptide biomarker ion with the highest significance was sequenced using LC-MS/MS and database searching and found to be associated with leucine-rich α-2-glycoprotein.
Description: This article is closed access.
Version: Published
DOI: 10.1002/prca.200800190
URI: https://dspace.lboro.ac.uk/2134/15895
Publisher Link: http://dx.doi.org/10.1002/prca.200800190
ISSN: 1862-8346
Appears in Collections:Closed Access (Chemistry)

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