A proteomic approach combining MS and bioinformatic analysis for the detection and identification of biomarkers of administration of exogenous human growth hormone in humans
Boateng, Joshua, Kay, Richard, Lancashire, Lee, Brown, Pamela, Velloso, Cristiana, Bouloux, Pierre, Teale, Phil, Roberts, Jane, Rees, Robert, Ball, Graham, Harridge, Stephen, Goldspink, Geoffrey and Creaser, Colin (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. ISSN 1862-8346 (Print), 1862-8354 (Online) (doi:10.1002/prca.200800190)Full text not available from this repository.
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 leudne-rich alpha-2-glycoprotein.
|Additional Information:|| Article first published online: 30 JUL 2009.  Published in print: August 2009.  Published in Proteomics - Clinical Applications, (2009), Volume 3, Issue 8, pp. 912–922. Issue published online: 18 AUG 2009|
|Uncontrolled Keywords:||bioinformatics, ESI-MS/MS, LC, MALDI, serum biomarkers|
|Subjects:||Q Science > Q Science (General)
Q Science > QD Chemistry
Q Science > QP Physiology
Q Science > QH Natural history > QH301 Biology
|School / Department / Research Groups:||School of Science
Faculty of Engineering & Science > School of Science
School of Science > Department of Pharmaceutical, Chemical & Environmental Sciences
Faculty of Engineering & Science > School of Science > Department of Pharmaceutical, Chemical & Environmental Sciences
|Last Modified:||24 May 2013 13:51|
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