Androgens and Glucuronidated Androgen Metabolites Are Associated with Metabolic Risk Factors in Men
Bibliographic record
Abstract
CONTEXT: Androgens are associated with metabolic risk factors in men. However, the independent impact of androgens and androgen metabolites on metabolic risk factors in men is unclear. OBJECTIVE: Our objective was to determine the predictive value of serum levels of androgens and glucuronidated androgen metabolites for metabolic risk factors. DESIGN AND STUDY SUBJECTS: We conducted a population-based study of two Swedish cohorts (1,068 young adult and 1,001 elderly men). MAIN OUTCOME MEASURES: We measured correlation of serum dihydrotestosterone (DHT), testosterone (T), and glucuronidated androgen metabolites with fat mass, fat distribution, serum lipids, and insulin resistance. RESULTS: Both DHT and T were negatively associated with different measures of fat mass in both cohorts (P < 0.001). Further statistical analysis indicated that DHT, but not T, was independently negatively associated with different measures of fat mass and insulin resistance (P < 0.001). The glucuronidated androgen metabolite androstane-3alpha,17beta-diol-17glucuronide (17G) was independently positively associated with fat mass (P < 0.001). Most importantly, the 17G to DHT ratio was strongly correlated, not only with fat mass but also with central fat distribution, intrahepatic fat, disturbed lipid profile, insulin resistance, and diabetes, explaining a substantial part of the total variance in total body fat (12% in young adult men, 15% in elderly men), the homeostasis model assessment index (10%), and high-density lipoprotein cholesterol (7%). CONCLUSION: Our findings demonstrate that 17-glucuronidation of the DHT metabolite androstane-3alpha,17beta-diol is strongly associated with several metabolic risk factors in men. Future longitudinal studies are required to determine the possible impact of the 17G to DHT ratio as a metabolic risk factor in men.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".