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Updated: Jun 18, 2026

Fecal Glucocorticoid Analysis: Non-invasive Adrenal Monitoring in Equids
Published on: April 25, 2016
Evaluation of plasma enzyme activities using gas chromatography-mass spectrometry based steroid signatures
Young Wan Ha1, Ju-Yeon Moon, Hyun-Jin Jung
1Life Sciences Division, Korean Institute of Science and Technology, 39-1 Hawolkok-dong, Seoul 136-791, Republic of Korea.
Abstract:
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 50min run. The devised method provided good linearity (correlation coefficient, r(2)>0.993), while the limit of quantification ranged from 0.2 to 2.0ngmL(-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 5alpha-reductase isoenzyme types 1 and 2. The levels of three plasma steroids, such as dihydrotestosterone, 5alpha-androstanedione and allotetrahydrocortisol, were decreased significantly after drug administration, while the levels of testosterone and 5beta-androstane-3beta,17alpha-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 5alpha-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.
