Development of models to predict anabolic response to testosterone administration in healthy young men.
Considerable heterogeneity exists in the anabolic response to androgen administration; however, the factors that contribute to variation in an individual's anabolic response to androgens remain unknown. We investigated whether testosterone dose and/or any combination of baseline variables, including concentrations of hormones, age, body composition, muscle function, and morphometry or polymorphisms in androgen receptor could explain the variability in anabolic response to testosterone. Fifty-four young men were treated with a long-acting gonadotropin-releasing hormone (GnRH) agonist and one of five doses (25, 50, 125, 300, or 600 mg/wk) of testosterone enanthate (TE) for 20 wk. Anabolic response was defined as a change in whole body fat-free mass (FFM) by dual-energy X-ray absorptiometry (DEXA), appendicular FFM (by DEXA), and thigh muscle volume (by magnetic resonance imaging) during TE treatment. We used univariate and multivariate analysis to identify the subset of baseline measures that best explained the variability in anabolic response to testosterone supplementation. The three-variable model of TE dose, age, and baseline prostate-specific antigen (PSA) level explained 67% of the variance in change in whole body FFM. Change in appendicular FFM was best explained (64% of the variance) by the linear combination of TE dose, baseline PSA, and leg press strength, whereas TE dose, log of the ratio of luteinizing hormone to testosterone concentration, and age explained 66% of the variation in change in thigh muscle volume. The models were further validated by using Ridge analysis and cross-validation in data subsets. Only the model using testosterone dose, age, and PSA was a consistent predictor of change in FFM in subset analyses. The length of CAG tract was only a weak predictor of change in thigh muscle volume and lean body mass. Hence, the anabolic response of healthy, young men to exogenous testosterone administration can largely be predicted by the testosterone dose.
Woodhouse
Linda J
LJ
Division of Endocrinology, Metabolism, and Molecular Medicine, Charles R. Drew University of Medicine and Science, 1731 E. 120th Street, Los Angeles, CA 90059, USA.
Reisz-Porszasz
Suzanne
S
Javanbakht
Marjan
M
Storer
Thomas W
TW
Lee
Martin
M
Zerounian
Hrant
H
Bhasin
Shalender
S
D015502:Absorptiometry, Photon; D000328:Adult; D001823:Body Composition / Q000187:drug effects*; D004305:Dose-Response Relationship, Drug; D004311:Double-Blind Method; D004334:Drug Administration Schedule; D005544:Forecasting; D012739:Gonadal Steroid Hormones / Q000008:administration & dosage / Q000097:blood / Q000494:pharmacology*; D006728:Hormones / Q000097:blood; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D008954:Models, Biological; D018482:Muscle, Skeletal / Q000033:anatomy & histology*; D009929:Organ Size / Q000187:drug effects; D009994:Osmolar Concentration; D011110:Polymorphism, Genetic; D011944:Receptors, Androgen / Q000235:genetics; D012016:Reference Values; D013739:Testosterone / Q000008:administration & dosage / Q000097:blood / Q000494:pharmacology*; D013848:Thigh
D012739:Gonadal Steroid Hormones; D006728:Hormones; D011944:Receptors, Androgen; D013739:Testosterone