Maternal <i>MTHFR</i> C677T Genotype & Depressed Mood during Pregnancy Affects <i>SLC6A4</i> Methylation in Infants at Birth
Bibliographic record
Abstract
In utero and early postnatal exposure to depressed maternal mood may program childhood behaviour via epigenetic processes. Methylenetetrahydrofolate reductase (MTHFR) is an enzyme important for methyl metabolism. A common variant in the MTHFR gene, C677T, is associated with depression. We investigated the effect of maternal MTHFR C677T genotype on maternal mood (Edinburgh Postnatal Depression Scale, EPDS), during pregnancy (n=82 women, all receiving folate supplements) and on promoter methylation of two genes implicated in depression, brain derived neurotrophic factor, BDNF , and sodium‐dependent serotonin transporter, SLC6A4 , in the women and their infants at birth. Women with the MTHFR 677TT genotype had greater ( P <0.05) mid gestational depressed mood (mean age 24.98±0.51 weeks). Maternal MTHFR 677TT genotype was also associated with lower ( P <0.05) maternal and infant SLC6A4 promoter methylation but not BDNF methylation. We also found a negative relationship ( P <0.01) between maternal depressed mood (EPDS scores) and maternal SLC6A4 promoter methylation. These findings show that maternal MTHFR C677T genotype and mood influence maternal and infant SLC6A4 promoter methylation and suggests that disrupted maternal methyl metabolism and depression during pregnancy affects gene‐specific DNA methylation patterns, which may have long‐term consequences for childhood behaviour. Grant Funding Source CIHR
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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".