Prenatal exposure to genocide accelerates epigenetic aging in third- and fourth-generation clocks among young adults in Rwanda
Bibliographic record
Abstract
Prenatal exposure genocide-related to trauma has been previously associated with increased morbidity. Whether the prenatal exposure to genocide and rape also impacts various aspects of biological regulation, including patterns of DNA methylation, remains unknown. The purpose of this study was to evaluate whether prenatal exposure to genocide-related trauma, including conception through rape, is associated with accelerated epigenetic aging, a molecular indicator of biological aging. We used a cross-sectional dataset to evaluate whether prenatal exposure to genocide or genocidal rape, among individuals conceived during the 1994 genocide against Tutsi in Rwanda were associated with differences in age acceleration in a range of clocks (first generation: Horvath and Hannum; second generation: PhenoAge; third generation: GrimAge and DunedinPace; and fourth generation: YingDamAge and YingAdaptAge), while taking into account exposure to adverse childhood experiences (ACEs). Participants were 24 years old during the time of data collection, and we enrolled 46 female and 45 male participants. Control participants were those of Rwandan descent who did not live in Rwanda during the genocide. We show that there are no differences in age acceleration observed with first- or second-generation age clocks. However, age acceleration was associated with prenatal exposure to extreme stress for all other clocks, with the greatest acceleration observed in the genocidal rape conception group. For the YingDamAge clock, acceleration effects were strengthened after the inclusion of ACEs. Our findings suggest that prenatal trauma exposure is associated with epigenetic age acceleration. Third and fourth-generation clocks may more accurately capture these relationships. Early life adverse experiences, including during prenatal development, are thought to reduce one’s lifespan. We evaluated whether mothers who experienced genocide related trauma during the 1994 genocide against Tutsi in Rwanda had children with faster biological aging. We measured biological aging using multiple epigenetic “clocks”, which calculates biological age, as opposed to chronological age, by looking at DNA changes across many genes. Our results showed that prenatal exposure to genocide-related trauma was associated with signs of faster aging for several epigenetic clocks. These findings suggest that supportive care and structural assistance for trauma-affected pregnant women and their children should be prioritized during human rights crises to mitigate these effects. Uwizeye et al. examine the association between epigenetic age and prenatal exposure to maternal stress related to genocide and genocidal rape. Findings reveal prenatal exposure to this type of maternal stress accelerates epigenetic aging and suggest that third and fourth-generation clocks more accurately capture these relationships.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".