Androgens and Parkinson's Disease: A Review of Human Studies and Animal Models
Bibliographic record
Abstract
Parkinson's disease (PD) is the second most common neurodegenerative disorder after Alzheimer's disease. A greater prevalence and incidence of PD are reported in men than in women, suggesting a potential contribution of sex, genetic difference and/or sex hormones. This review presents an overview of epidemiological and clinical studies investigating sex differences in the incidence and symptoms of PD. This sex difference is replicated in animal models of PD showing an important neuroprotective role of sex steroids. Therefore, although gender and genetic factors likely contribute to the sex difference in PD, focus here will be on sex hormones because of their neuroprotective role. Androgens receive less attention than estrogen. It is well known that endogenous androgens are more abundant in healthy men than in women and decrease with aging; lower levels are reported in PD men than in healthy male subjects. Drug treatments with androgens, androgen precursors, antiandrogens, and drugs modifying androgen metabolism are available to treat various endocrine conditions, thus having translational value for PD but none have yet given sufficient positive effects for PD. Variability in the androgen receptor is reported in humans and is an additional factor in the response to androgens. In animal models of PD used to study neuroprotective activity, the androgens testosterone and dihydrotestosterone have given inconsistent results. 5α-Reductase inhibitors have shown neuroprotective activity in animal models of PD and antidyskinetic activity. Hence, androgens have not consistently shown beneficial or deleterious effects in PD but numerous androgen-related drugs are available that could be repurposed for PD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".