Ancestral stress programs sex-specific biological aging trajectories and non-communicable disease risk
Bibliographic record
Abstract
The incidence of non-communicable diseases (NCDs) is rising globally but their causes are generally not understood. Here we show that cumulative ancestral stress leads to premature aging and raises NCD risk in a rat population. This longitudinal study revealed that cumulative multigenerational prenatal stress (MPS) across four generations (F0-F3) raises age- and sex-dependent adverse health outcomes in F4 offspring. MPS accelerated biological aging processes and exacerbated sex-specific incidences of respiratory and kidney diseases, inflammatory processes and tumors. Unbiased deep sequencing of frontal cortex revealed that MPS altered expression of microRNAs and their target genes involved in synaptic plasticity, stress regulation, immune function and longevity. Multi-layer top-down deep learning metabolite enrichment analysis of urine markers revealed altered metabolic homeodynamics in MPS males. Thus, peripheral metabolic signatures may provide sensitive biomarkers of stress vulnerability and disease risk. Programming by MPS appears to be a significant determinant of lifetime mental health trajectories, physical wellbeing and vulnerability to NCDs through altered epigenetic regulation.
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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 | 0.000 |
| 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".