Prenatal Alcohol Exposure: Foetal Programming, the Hypothalamic‐Pituitary‐Adrenal Axis and Sex Differences in Outcome
Bibliographic record
Abstract
Prenatal exposure to alcohol has adverse effects on offspring neuroendocrine and behavioural functions. Alcohol readily crosses the placenta, thus directly affecting developing foetal endocrine organs. In addition, alcohol-induced changes in maternal endocrine function can disrupt the normal hormonal interactions between the pregnant female and foetal systems, altering the normal hormone balance and, indirectly, affecting the development of foetal metabolic, physiological and endocrine functions. The present review focuses on the adverse effects of prenatal alcohol exposure on offspring neuroendocrine function, with particular emphasis on the hypothalamic-pituitary-adrenal (HPA) axis, a key player in the stress response. The HPA axis is highly susceptible to programming during foetal and neonatal development. Here, we review data demonstrating that alcohol exposure in utero programmes the foetal HPA axis such that HPA tone is increased throughout life. Importantly, we show that, although alterations in HPA responsiveness and regulation are robust phenomena, occurring in both male and female offspring, sexually dimorphic effects of alcohol are frequently observed. We present updated findings on possible mechanisms underlying differential effects of alcohol on male and female offspring, with special emphasis on effects at different levels of the HPA axis, and on modulatory influences of the hypothalamic-pituitary-gonadal hormones and serotonin. Finally, possible mechanisms underlying foetal programming of the HPA axis, and the long-term implications of increased exposure to endogenous glucocorticoids for offspring vulnerability to illnesses or disorders later in life are discussed.
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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) | 0.000 | 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 | 0.000 |
| 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".