Antenatal Glucocorticoid Exposure Results in Sex-Specific and Transgenerational Changes in Prefrontal Cortex Gene Transcription that Relate to Behavioural Outcomes
Bibliographic record
Abstract
Abstract Synthetic glucocorticoids (sGC) are administered to women at risk for pre-term delivery to reduce respiratory distress syndrome in the newborn. The prefrontal cortex (PFC) is important in regulating stress responses and related behaviours and expresses high levels of glucocorticoid receptors (GR). Further, antenatal exposure to sGC results in a hyperactive phenotype in first generation (F1) juvenile male and female offspring, as well as F2 and F3 juvenile females from the paternal lineage. We hypothesized that multiple courses of antenatal sGC modify gene expression in the PFC, that these effects are sex-specific and maintained across multiple generations, and that the gene sets affected relate to modified locomotor activity. We performed RNA sequencing on PFC of F1 juvenile males and females, as well as F2 and F3 juvenile females from the paternal lineage and used regression modelling to relate gene expression and behavior. Antenatal sGC resulted in sex-specific and generation-specific changes in gene expression. Further, the expression of 4 genes (C9orf116, Calb1, Glra3, and Gpr52) explained 20–29% of the observed variability in locomotor activity. Antenatal exposure to sGC profoundly influences the developing PFC; effects are evident across multiple generations and may drive altered behavioural phenotypes.
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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 | 0.000 | 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 | 0.000 |
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".