Adult Glucocorticoid Exposure Leads to Transcriptional and DNA Methylation Changes in Nuclear Steroid Receptors in the Hippocampus and Kidney of Mouse Male Offspring1
Bibliographic record
Abstract
Synthetic glucocorticoids (sGCs) are commonly prescribed for the management of inflammatory and endocrine disorders. However, nothing is known regarding the effects of sGC on adult germline methylome and whether these effects can be transmitted to the next generation. We hypothesized that administration of sGC to adult male mice alters DNA methylation in mature sperm and modifies the transcription and methylation of steroid receptors in male F1 offspring. Adult C57BL/6 males (n = 10/group) were injected on five consecutive days with 1 mg/kg sGC (i.e., dexamethasone) or vehicle and euthanized 35 or 60 days after initial treatment or bred with control females (60 days postinitial treatment; n = 5/group). A significant increase in global non-CpG methylation was observed in F0 sperm 60 days following sGC treatment. In the hippocampus and kidney of Postnatal Day 50 (PND50) and PND240 male offspring derived from fathers exposed to sGC, significant differences in mineralocorticoid receptor (Nr3c2; Mr), estrogen alpha receptor (Nr3a1; Ers1), and glucocorticoid receptor (Nr3c1; Gr) expression were observed. Furthermore, significant demethylation in regulatory regions of Mr, Gr, and Esr1 was observed in the PND50 kidney derived from fathers exposed to sGC. This is the first demonstration that paternal pharmacological exposure to sGC can alter the expression and DNA methylation of nuclear steroid receptors in brain and somatic tissues of offspring. These findings provide proof of principle that adult male exposure to sGC can affect DNA methylation and gene expression in offspring, indicating the possibility that adult experiences that evoke increases in endogenous glucocorticoid (i.e., stress) might have similar effects.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".