Metabolomic Profiling of Biomarkers Indicative of Ancestral and Lifetime Adversity in a Two-Hit Stress Model
Bibliographic record
Abstract
Introduction: Chronic prenatal maternal stress (PNMS) can have adverse effects on the developing fetus and lifetime health. The effects depend on the number of stressors individuals are exposed to. Over-activation of the mother’s stress response also potentially triggers epigenetic marks that can be transmitted to several generations of offspring. To date, very little research has focused on how exposure to ancestral PNMS affects an individual’s response to both chronic and acute stress throughout their lifetime. The purpose of this study was to investigate if exposure to ancestral PNMS puts an individual at an evolutionary advantage or disadvantage with respect to their altered stress response. This study utilized a rat model of ancestral PNMS to explore the response of the metabolome to both acute and chronic stress. Methods: Forty-eight male rats from the third filial generation were derived from three different lineages: (1) a transgenerational PNMS lineage where only the F0 mother was exposed to stress; (2) a multigenerational PNMS lineage where the mother from each generation was exposed to stress; and (3) a control lineage where there was no experimental stress exposure. Each of these groups were split in two; an acute stress group and a chronic stress group. Plasma was collected from each animal, processed to extract the water-soluble metabolites, added to NMR buffer, and pipetted into NMR tubes. NMR spectra were acquired and the data underwent a data reduction step (binning), normalization, scaling, and both univariate and multivariate statistical testing. These tests identified spectral peaks from metabolites that had been significantly altered across comparison groups. Chemometric software was utilized to determine the identity of altered metabolites and pathway topology analysis was performed. Results: Multivariate and univariate statistical tests indicated that exposure to chronic stress in ancestrally stressed rats creates significant alteration in the metabolomic profile when compared to control animals. No differences were observed in the case of acute stress. Conclusions: Our results support the hypothesis that ancestral and lifetime stress cumulatively affect the metabolome. A subset of metabolites can potentially act as biomarkers of stress during pregnancy. This procedure may aid in the development of new predictive and diagnostic strategies in precision medicine approaches. *Indicates presenter
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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) | 0.001 | 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".