Complex disease, gender and epigenetics
Bibliographic record
Abstract
Gender differences in susceptibility to complex disease such as asthma, diabetes, lupus, autism and major depression, among numerous other disorders, represent one of the hallmarks of non-Mendelian biology. It has been generally accepted that endocrinological differences are involved in the sexual dimorphism of complex disease; however, specific molecular mechanisms of such hormonal effects have not been elucidated yet. This paper will review evidence that sex hormone action may be mediated via gene-specific epigenetic modifications of DNA and histones. The epigenetic modifications can explain sex effects at DNA sequence polymorphisms and haplotypes identified in gender-stratified genetic linkage and association studies. Hormone-induced DNA methylation and histone modification changes at specific gene regulatory regions may increase or reduce the risk of a disease. The epigenetic interpretation of sexual dimorphism fits well into the epigenetic theory of complex disease, which argues for the primary pathogenic role of inherited and/or acquired epigenetic misregulation rather than DNA sequence variation. The new experimental strategies, especially the high throughput microarray-based epigenetic profiling, can be used for testing the epigenetic hypothesis of gender effects in complex diseases.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".