Maternal psychosocial risk factors and child gestational epigenetic age in a South African birth cohort study
Bibliographic record
Abstract
Accelerated epigenetic aging relative to chronological age has been found to be associated with higher risk of mortality in adults. However, little is known about whether and how in utero exposures might shape child gestational epigenetic age (EA) at birth. We aimed to explore associations between maternal psychosocial risk factors and deviation in child gestational EA at birth (i.e., greater or lower EA relative to chronological age) in a South African birth cohort study-the Drakenstein Child Health Study. Maternal psychosocial risk factors included trauma/stressor exposure; posttraumatic stress disorder (PTSD); depression; psychological distress; and alcohol/tobacco use. Child gestational EA at birth was calculated using an epigenetic clock previously devised for neonates; and gestational EA deviation was calculated as the residuals of the linear model between EA and chronological gestational age. Bivariate linear regression was then used to explore unadjusted associations between maternal/child risk factors and child gestational EA residuals at birth. Thereafter, a multivariable regression method was used to determine adjusted associations. Data from 271 maternal-child dyads were included in the current analysis. In the multivariable regression model, maternal PTSD was significantly and negatively associated with child gestational EA residuals at birth (β = -1.95; p = 0.018), controlling for study site, sex of the child, head circumference at birth, birthweight, mode of delivery, maternal estimated household income, body mass index (BMI) at enrolment, HIV status, anaemia, psychological distress, and prenatal tobacco or alcohol use. Given the novelty of this preliminary finding, and its potential translational relevance, further studies to delineate underlying biological pathways and to explore clinical implications of EA deviation are warranted.
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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".