4.5 Article

Evaluation of plasma enzyme activities using gas chromatography-mass spectrometry based steroid signatures

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.jchromb.2009.11.010

Keywords

Steroid; Plasma; Enzyme activity; GC-MS; Metabolite profiling

Funding

  1. Korean Institute of Science and Technology (KIST)
  2. Korean Ministry of Education, Science and Technology (MEST)
  3. Korean Science and Engineering Foundation (KOSEF)
  4. National Research Foundation of Korea [2009-0082198, 2004-2002145] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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The simultaneous quantification of 65 plasma steroids, including 22 androgens, 15 estrogens, 15 corticoids and 13 progestins, was developed using gas chromatography-mass spectrometry (GC-MS). The extraction efficiency of the catechol estrogens was improved by the addition Of L-ascorbic acid in several steps. All steroids, as their trimethylsilyl derivatives, were well separated with good peak shapes within a 50 min run. The devised method provided good linearity (correlation coefficient, r(2) > 0.993), while the limit of quantification ranged from 0.2 to 2.0 ng mL(-1). The precision (% CV) and accuracy (% bias) were 2.0-12.4% and 93.5-109.2%, respectively. The metabolic changes were evaluated by applying this method to plasma samples obtained from 26 healthy male subjects grouped according to the pre- and post-administration of dutasteride, which inhibits 5 alpha-reductase isoenzyme types 1 and 2. The levels of three plasma steroids, Such as dihydrotestosterone, 5 alpha-androstanedione and allotetrahydrocortisol, were decreased significantly after drug administration, while the levels of testosterone and 5 beta-androstane-3 beta, 17 alpha-diol were increased. In addition, the ratios of the steroid precursors and their metabolites, which represent the activities of the related enzymes, were z-score transformed for visualization in heat maps generated using Supervised hierarchical clustering analysis. These results validated the data transformation because 5 alpha-reductase is an indicator for the biological actions of dutasteride. GC-MS base quantitative visualization might be found in the integration with the mining biomarkers in drug evaluations and hormone-dependent diseases. (C) 2009 Elsevier B.V. All rights reserved.

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