Premium
A proteomic approach combining MS and bioinformatic analysis for the detection and identification of biomarkers of administration of exogenous human growth hormone in humans
Author(s) -
Boateng Joshua,
Kay Richard,
Lancashire Lee,
Brown Pamela,
Velloso Cristiana,
Bouloux Pierre,
Teale Phil,
Roberts Jane,
Rees Robert,
Ball Graham,
Harridge Stephen,
Goldspink Geoffrey,
Creaser Colin
Publication year - 2009
Publication title -
proteomics – clinical applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.948
H-Index - 54
eISSN - 1862-8354
pISSN - 1862-8346
DOI - 10.1002/prca.200800190
Subject(s) - placebo , peptide , biomarker , proteomics , biomarker discovery , glycoprotein , medicine , endocrinology , quantitative proteomics , recombinant dna , human growth hormone , growth hormone , hormone , chemistry , chromatography , biochemistry , pathology , gene , alternative medicine
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.