DNA methylation mediates the effect of exposure to prenatal maternal stress on cytokine production in children at age 13½ years: Project Ice Storm
Bibliographic record
Abstract
BACKGROUND: Prenatal maternal stress (PNMS) is an important programming factor of postnatal immunity. We tested here the hypothesis that DNA methylation of genes in the NF-κB signaling pathway in T cells mediates the effect of objective PNMS on Th1 and Th2 cytokine production in blood from 13½ year olds who were exposed in utero to the 1998 Quebec ice storm. RESULTS: Bootstrapping analyses were performed with 47 CpGs across a selection of 20 genes for Th1-type cytokines (IFN-γ and IL-2) and Th2-type cytokines (IL-4 and IL-13). Six CpGs in six different NF-κB signaling genes (PIK3CD, PIK3R2, NFKBIA, TRAF5, TNFRSF1B, and LTBR) remained as significant negative mediators of objective PNMS on IFN-γ secretion after correcting for multiple comparisons. However, no mediation effects on IL-2, IL-4 and IL-13 survived Bonferroni correction. CONCLUSIONS: The present study provides preliminary evidence supporting the mediating role of DNA methylation in the association between objective aspects of PNMS and child immune states, favoring a Th2 shift.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".