Steroid hormone-mediated epigenetic programming during puberty: uncovering links to depression
Bibliographic record
Abstract
DNA methylation (DNAm) is a key epigenetic modification that dynamically regulates eukaryotic development over time. DNAm has been found to influence a variety of biological processes in both normative and pathological states, such as depression. Since DNAm can serve as an interface between environmental influence and gene expression, it is a mechanism studied in the context of many pathologies, including psychiatric. Depression is a complex and heterogeneous disorder strongly influenced by puberty, as evidenced by increased rates in both sexes after sexual maturation. However, this effect is more pronounced in females, contributing to its twofold increased lifetime prevalence compared to males. Additionally, depression is consistently associated with altered DNAm at specific genomic sites. In this review, we discuss how DNAm programming can affect functional pathways during puberty and in turn, influence disease outcomes. Here, we highlight the bidirectional relationship of steroid hormone surges during this sensitive period and DNAm, adding a layer of complexity and insight into the pathophysiology of depression. Specifically, we explore the extent of DNAm change throughout puberty, how it contributes to individual and sex-specific differences in puberty, and how it may influence the risk for depression.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".