DNA methylation differences between cord and adult white blood cells reflect postnatal immune cell maturation
Bibliographic record
Abstract
Epigenetic modifications such as DNA methylation are both cell type and developmental age specific. Here, we show that the immunological maturation of blood cell types influences DNA methylation changes from naive cord blood to fully functional adult blood. Lymphoid cells in adult blood showed more variability than in cord blood suggesting an antigen-dependent maturation of DNA methylation in lymphoid cells throughout the lifespan. Fewer DNA methylation changes between cord and adult blood were observed in myeloid cells, particularly in monocytes, which demonstrated the least number of DNA methylation changes between cord and adult blood. We also noted differences in epigenetic ages by immune cell types within the same individuals, specifically in cord blood where monocytes were epigenetically oldest compared to the other cell types. In addition, we provide a publicly available resource to the community as an R Shiny web application to interactively explore epigenetic patterns between naive cord white blood cells and fully functional adult white blood cells for six immune cell types. Comparison of DNA methylation profiles from isolated cell types of cord and adult blood reveals that lymphoid cells develop antigen-driven epigenetic variability during maturation, while myeloid cells, especially monocytes, are more stable.
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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) | 0.005 | 0.001 |
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".