The Influence of Trinucleotide Repeats in the Androgen Receptor Gene on Androgen-related Traits and Diseases
Bibliographic record
Abstract
CONTEXT: Trinucleotide repeats in the androgen receptor have been proposed to influence testosterone signaling in men, but the clinical relevance of these trinucleotide repeats remains controversial. OBJECTIVE: To examine how androgen receptor trinucleotide repeat lengths affect androgen-related traits and disease risks and whether they influence the clinical importance of circulating testosterone levels. METHODS: We quantified CAG and GGC repeat lengths in the androgen receptor (AR) gene of European-ancestry male participants in the UK Biobank from whole-genome and whole-exome sequence data using ExpansionHunter and tested associations with androgen-related traits and diseases. We also examined whether the associations between testosterone levels and these outcomes were affected by adjustment for the repeat lengths. RESULTS: We successfully quantified the repeat lengths from whole-genome and/or whole-exome sequence data in 181 217 males. Both repeat lengths were shown to be positively associated with circulating total testosterone level and bone mineral density, whereas CAG repeat length was negatively associated with male-pattern baldness, but their effects were relatively small and were not associated with most of the other outcomes. Circulating total testosterone level was associated with various outcomes, but this relationship was not affected by adjustment for the repeat lengths. CONCLUSION: In this large-scale study, we found that longer CAG and GGC repeats in the AR gene influence androgen resistance, elevate circulating testosterone level via a feedback loop, and play a role in some androgen-targeted tissues. Generally, however, circulating testosterone level is a more important determinant of androgen action in males than repeat lengths.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".