Maternal depression is associated with DNA methylation changes in cord blood T lymphocytes and adult hippocampi
Bibliographic record
Abstract
Depression affects 10-15% of pregnant women and has been associated with preterm delivery and later developmental, behavioural and learning disabilities. We tested the hypothesis that maternal depression is associated with DNA methylation alterations in maternal T lymphocytes, neonatal cord blood T lymphocytes and adult offspring hippocampi. Genome-wide DNA methylation of CD3+ T lymphocytes isolated from 38 antepartum maternal and 44 neonatal cord blood samples were analyzed using Illumina Methylation 450 K microarrays. Previously obtained methylation data sets using methylated DNA immunoprecipitation and array-hybridization of 62 postmortem hippocampal samples of adult males were re-analyzed to test associations with history of maternal depression. We found 145 (false discovery rate (FDR) q<0.05) and 2520 (FDR q<0.1) differentially methylated CG-sites in cord blood T lymphocytes of neonates from the maternal depression group as compared with the control group. However, no significant DNA methylation differences were detected in the antepartum maternal T lymphocytes of our preliminary data set. We also detected 294 differentially methylated probes (FDR q<0.1) in hippocampal samples associated with history of maternal depression. We observed a significant overlap (P=0.002) of 33 genes with changes in DNA methylation in T lymphocytes of neonates and brains of adult offspring. Many of these genes are involved in immune system functions. Our results show that DNA methylation changes in offspring associated with maternal depression are detectable at birth in the immune system and persist to adulthood in the brain. This is consistent with the hypothesis that system-wide epigenetic changes are involved in life-long responses to maternal depression in the offspring.
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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 | 0.001 |
| 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) | 0.001 | 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".