Preliminary indications that the Attachment and Biobehavioral Catch-up Intervention alters DNA methylation in maltreated children
Bibliographic record
Abstract
Maltreatment during development is associated with epigenetic changes to the genome. Enhancing caregiving may mitigate these effects. Attachment and Biobehavioral Catch-Up (ABC) is an intervention that has been shown to improve parent-child relationships and a variety of biological and behavioral outcomes among children that are involved in Child Protective Services. This preliminary study, using a small sample size, explored whether children who received ABC exhibit different methylation patterns than those who received a control intervention. The participants included 23 children aged 6-21 months who were randomized to receive ABC (n = 12) or a control intervention (n = 11). While the children displayed similar methylation patterns preintervention, DNA methylation varied between the ABC and control groups at 14,828 sites postintervention. Functional pathway analyses indicated that these differences were associated with gene pathways that are involved in cell signaling, metabolism, and neuronal development. This study is one of the first to explore parenting intervention effects on children's DNA methylation at the whole genome level in infancy. These preliminary findings provide a basis for hypothesis generation in further research with larger-scale studies regarding the malleability of epigenetic states that are associated with maltreatment.
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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 | 0.002 |
| 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) | 0.005 | 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".