Analysis of anabolic steroids in human hair using LC–MS/MS
Autor: | Declan P. Naughton, Nawed Deshmukh, Iltaf Hussain, Andrea Petróczi, James Barker |
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Rok vydání: | 2010 |
Předmět: |
Male
Urinalysis Anabolism Clinical Biochemistry Enzyme-Linked Immunosorbent Assay Tandem mass spectrometry Biochemistry Anabolic Agents Endocrinology Tandem Mass Spectrometry Lc ms ms medicine Humans Nandrolone Blood testing Molecular Biology Stanozolol Doping in Sports Pharmacology Chromatography medicine.diagnostic_test Chemistry Organic Chemistry Hair analysis Reproducibility of Results Female Chromatography Liquid Hair medicine.drug |
Zdroj: | Steroids. 75:710-714 |
ISSN: | 0039-128X |
DOI: | 10.1016/j.steroids.2010.04.007 |
Popis: | New highly sensitive, specific, reliable, reproducible and robust LC-MS/MS methods were developed to detect the anabolic steroids, nandrolone and stanozolol, in human hair for the first time. Hair samples from 180 participants (108 males, 72 females, 62% athletes) were screened using ELISA which revealed 16 athletes as positive for stanozolol and 3 for nandrolone. Positive samples were confirmed on LC-MS/MS in selective reaction monitoring (SRM) mode. The assays for stanozolol and nandrolone showed good linearity in the range 1 to 400 pg/mg and 5 to 400 pg/mg respectively. The methods were validated for LLOD, interday precision, intraday precision, specificity, extraction recovery and accuracy. The assays were capable of detecting 0.5 pg stanozolol and 3.0 pg nandrolone per mg of hair, when approximately 20mg of hair were processed. Analysis using LC-MS/MS confirmed eleven athletes' positive for stanozolol (5.0 pg/mg to 86.3 pg/mg) and 1 for nandrolone (14.0 pg/mg) thus avoiding false results from ELISA screening. The results obtained demonstrate the application of these hair analysis methods to detect both steroids at low concentrations, hence reducing the amount of hair required significantly. The new methods complement urinalysis or blood testing and facilitate improved doping testing regimes. Hair analysis benefits from non invasiveness, negligible risk of infection and facile sample storage and collection, whilst reducing risks of tampering and cross contamination. Owing to the wide detection window, this approach may also offer an alternative approach for out-of-competition testing. |
Databáze: | OpenAIRE |
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