One of the new generation of drugs abused by sports performers and bodybuilders is recombinant human growth hormone (rhGH) which complements the endogenous growth hormone (hGH) that is produced naturally by the body. It is taken to increase muscle mass and decrease body fat although the US Drug Enforcement Agency declared that "the ability of hGH to increase athletic performance is debatable."

Nevertheless, it is a banned substance in the sports arena. rhGH is also prescribed illegally to aging adults who see it as a way to replenish declining hGH levels and reduce the effects of aging. The illicit use of synthetic hGH is believed to be widespread because it is difficult to detect.

rhGH and natural hGH are structurally identical, which limits the detection options. They also have a short half-life and natural hGH is released by the pituitary gland in a pulsating manner, so that the detection window is small. In addition, the circulating levels of hGH can be increased up to 70-fold by acute exercise.

Current methods for detecting rhGH misuse involve enzyme-linked immunosorbent assay, using either the ratio of two different GH isoforms or biomarkers produced by GH administration. Now, a team of scientists based in the UK has applied mass spectrometry to the problem in an approach based on proteomics techniques. The study was carried out by Colin Creaser from Loughborough University with co-workers from Nottingham Trent University, Quotient Bioresearch Ltd. and University College London.

A daily dose of rhGH or a placebo was administered to eight men over two weeks then blood samples were taken before and immediately after a period of exercise, then again 2.5 hours later. The serum was collected and submitted to two complementary analyses.

In the first instance, serum was simply diluted and analysed directly by MALDI mass spectrometry, revealing a complex mixture of protein ions. Alternatively, serum was depleted of the high-abundant and high-molecular-mass proteins using acetonitrile before digestion of the remaining proteins with trypsin. The peptide mixtures that were produced were analysed by LC/MS with electrospray ionisation, with spectra summing from 12.5-55 minutes to remove retention time as a source of error. Highly complex spectra were obtained.

Both sets of data were subjected to artificial neural network analysis (ANN). In a stepwise approach, the MALDI data produced a set of six protein ions which together correctly predicted 96% of samples into their correct groups, drugged or placebo. The sensitivity was 91%, with 20 of the 22 drug samples correct, and the specificity was 100% for all 24 control samples.

Similarly, the LC/MS data revealed a set of six peptide ions that correctly classified 93% of all samples, with a sensitivity and specificity of 90% and 95%, respectively.

Closer examination of the data showed that the protein ion at m/z 17,310 had a very strong discriminatory response, its intensity being lower in treated serum than in controls. In the LC/MS peptide data, the ion at m/z 741.2 increased in treated serum compared with controls and had the highest significance in the model, with a predictive accuracy of 84%.

Subsequent identification of this peptide ion by tandem mass spectrometry revealed it to be a tryptic fragment from leucine-rich alpha-2-glycoprotein (LRG). This ion was not observed in the MALDI mass spectrum because its molecular mass exceeded the m/z range of the instrument.

Two further ions from LRG were detected and together the three peptides corresponded to 20% of the protein sequence. They all increased in intensity after rhGH administration, seeming to confirm that the protein is rhGH dependent.

Even so, further examination of the data showed that monitoring this protein alone would not enable complete discrimination between rhGH-treated and control individuals. Inclusion of the known rhGH biomarker IGF-1 as well as LRG improved the discrimination.

The team remarked that further validation with a larger sample set is required before LRG can be added to the list of rhGH biomarkers. This initial study which the researchers believe to be the first reported use of ANNs in biomarker discovery using LC/MS data, demonstrates the potential of proteomics with ANN for detecting biomarkers of drugs of abuse in sports.

Related links:

• Proteomics - Clinical Applications 2009, 3, 912-922: "A proteomic approach combining MS and bioinformatic analysis for the detection and identification of biomarkers of administration of exogenous human growth hormone in humans"

Article by Steve Down

The views represented in this article are solely those of the author and do not necessarily represent those of John Wiley and Sons, Ltd.